From 9aeabd0f00e81581d4e9cf0fc8246c505be87aa1 Mon Sep 17 00:00:00 2001 From: David Meijer Date: Wed, 3 Sep 2025 16:28:36 +0200 Subject: [PATCH 01/65] UPD: v1.0.1 -> v2.0.0 --- app/src/client/package.json | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/app/src/client/package.json b/app/src/client/package.json index a81aae2..ddeb0f9 100644 --- a/app/src/client/package.json +++ b/app/src/client/package.json @@ -1,6 +1,6 @@ { "name": "paras-webapp", - "version": "1.0.1", + "version": "2.0.0", "private": true, "dependencies": { "@emotion/react": "^11.13.3", From 477a51b6c7ce50b5e512646f6b04e5f1dd6a7801 Mon Sep 17 00:00:00 2001 From: David Meijer Date: Thu, 4 Sep 2025 16:39:17 +0200 Subject: [PATCH 02/65] WIP: updating docker installation --- app/Dockerfile.client | 20 ++-- app/Dockerfile.server | 55 +++++++---- app/docker-compose.yml | 10 +- app/server-environment.yml | 17 ++++ ...quirements.txt => server-requirements.txt} | 2 +- app/src/client/deployment/nginx.default.conf | 93 ++++++++++++------- app/src/client/package-lock.json | 8 +- 7 files changed, 136 insertions(+), 69 deletions(-) create mode 100644 app/server-environment.yml rename app/{src/server/requirements.txt => server-requirements.txt} (56%) diff --git a/app/Dockerfile.client b/app/Dockerfile.client index dc4a534..5529c33 100644 --- a/app/Dockerfile.client +++ b/app/Dockerfile.client @@ -2,17 +2,23 @@ # Provides proxies / api requests # Build React frontend -FROM node:16-alpine as build-step +FROM node:20-alpine as build WORKDIR /app -ENV PATH /app/node_modules/.bin:$PATH + +# Install dependencies with cache-friendly order COPY ./src/client/package.json ./src/client/package-lock.json ./ +RUN npm ci + +# Build COPY ./src/client/src ./src COPY ./src/client/public ./public -RUN npm install RUN npm run build -COPY ./src/client/deployment/nginx.default.conf /etc/nginx/conf.d/default.conf -# Build nginx container +# Nginx runtime FROM nginx:stable-alpine -COPY --from=build-step ./app/build /usr/share/nginx/html -COPY --from=build-step ./etc/nginx/conf.d/default.conf /etc/nginx/conf.d/default.conf \ No newline at end of file + +COPY --from=build /app/build /usr/share/nginx/html +COPY ./src/client/deployment/nginx.default.conf /etc/nginx/conf.d/default.conf + +EXPOSE 80 +CMD ["nginx", "-g", "daemon off;"] \ No newline at end of file diff --git a/app/Dockerfile.server b/app/Dockerfile.server index 16edf64..5b28c80 100644 --- a/app/Dockerfile.server +++ b/app/Dockerfile.server @@ -1,25 +1,42 @@ -# This Dockerfile builds API only -FROM python:3.9 +# Use Mambaforge for fast, reliable conda solves (includes mamba) +FROM condaforge/mambaforge:24.9.2-0 -WORKDIR /app -COPY ./src/server/ ./ -RUN pip install -r ./requirements.txt -ENV FLASK_ENV production +# Make non-interactive shells load conda env nicely +SHELL ["/bin/bash", "-lc"] -EXPOSE 4009 +# Create a non-root user for saner file permissions +ARG USERNAME=app +ARG USER_UID=1000 +ARG USER_GID=$USER_UID +RUN groupadd --gid $USER_GID $USERNAME \ + && useradd --uid $USER_UID --gid $USER_GID -m $USERNAME -# Install HMMER2 -RUN apt-get update -RUN apt-get install -y hmmer2 +# Workdir +WORKDIR /app -# Install MUSCLE -RUN mkdir muscle -WORKDIR /app/muscle -RUN wget https://drive5.com/muscle/muscle_src_3.8.1551.tar.gz -RUN tar -xvzf muscle_src_3.8.1551.tar.gz -RUN make -RUN cp muscle /usr/local/bin/muscle +# Copy env first to leverage Docker layer caching +COPY server-environment.yml /app/ +COPY server-requirements.txt /app/ -WORKDIR /app +# Create Conda env with mamba (faster) and clean caches +RUN mamba env create -n web -f server-environment.yml \ + && conda clean -afy + +# Ensure `conda run -n web ...` works for ENTRYPOINT/CMD +RUN echo "conda activate web" >> /etc/bash.bashrc + +# Copy the app code and give ownership to the non-root user +COPY --chown=${USER_UID}:${USER_GID} ./src/server/ /app/ + +# Ensure temp dir exists and is writable +RUN mkdir -p /app/temp && chown -R ${USER_UID}:${USER_GID} /app + +# Use the unprivileged user at runtime +USER $USERNAME + +# Expose your service port +EXPOSE 4009 -CMD ["sh", "-c", "gunicorn -b :4009 --timeout 120 api:app"] \ No newline at end of file +# Run everything inside the conda env without needing manual activation +ENTRYPOINT ["conda", "run", "--no-capture-output", "-n", "web"] +CMD ["gunicorn", "-b", ":4009", "--timeout", "120", "api:app"] diff --git a/app/docker-compose.yml b/app/docker-compose.yml index bf4d0e1..5822c12 100644 --- a/app/docker-compose.yml +++ b/app/docker-compose.yml @@ -9,11 +9,10 @@ services: restart: always container_name: paras-server volumes: - - ./models:/app/models + - ./models:/app/models:rw environment: - MODEL_DIR=/app/models - networks: - - paras-network + networks: [paras-network] paras-client: build: @@ -24,8 +23,9 @@ services: - "4010:80" restart: always container_name: paras-client - networks: - - paras-network + networks: [paras-network] + depends_on: + - paras-server networks: paras-network: diff --git a/app/server-environment.yml b/app/server-environment.yml new file mode 100644 index 0000000..ad41d20 --- /dev/null +++ b/app/server-environment.yml @@ -0,0 +1,17 @@ +name: web +channels: + - conda-forge + - bioconda +dependencies: + # Python runtime + - python=3.9 + + # Bio tools (from bioconda) + - hmmer # HMMER v3 (hmmsearch, hmmscan, hmmpress, etc.) + - hmmer2 # HMMER v2 (e.g., hmmpfam, hmmsearch from v2 toolset) + - muscle=3.8.1551 # MUSCLE aligner + + # Extra PyPI deps + - pip + - pip: + - -r /app/server-requirements.txt diff --git a/app/src/server/requirements.txt b/app/server-requirements.txt similarity index 56% rename from app/src/server/requirements.txt rename to app/server-requirements.txt index 09d2d96..7a3c323 100644 --- a/app/src/server/requirements.txt +++ b/app/server-requirements.txt @@ -6,4 +6,4 @@ flask_sqlalchemy gunicorn joblib apscheduler -git+https://github.com/BTheDragonMaster/parasect@webapp \ No newline at end of file +git+https://github.com/BTheDragonMaster/parasect@webapp_dev_docker \ No newline at end of file diff --git a/app/src/client/deployment/nginx.default.conf b/app/src/client/deployment/nginx.default.conf index 478fd18..f7f480b 100644 --- a/app/src/client/deployment/nginx.default.conf +++ b/app/src/client/deployment/nginx.default.conf @@ -1,37 +1,64 @@ -# nginx configuration for Docker. +# nginx configuration for Docker (React SPA + API proxy) server { - listen 80; - server_name localhost; - root /usr/share/nginx/html; - index index.html; - error_page 500 502 503 504 /50x.html; - - location / { - try_files $uri $uri/ /index.html$is_args$args =404; # https://stackoverflow.com/questions/43555282/react-js-application-showing-404-not-found-in-nginx-server - add_header Cache-Control "no-cache"; - } + listen 80; + server_name _; - location /static { - expires 1y; - add_header Cache-Control "public"; - } + root /usr/share/nginx/html; + index index.html; + + # Serve static assets with long cache (immutable) + location /static/ { + try_files $uri =404; + access_log off; + expires 1y; + add_header Cache-Control "public, max-age=31536000, immutable"; + } + + # API proxy + location /api/ { + proxy_pass http://paras-server:4009; # do not add slash at end! + + # pass-thru headers + proxy_set_header Host $host; + proxy_set_header X-Real-IP $remote_addr; + proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for; + proxy_set_header X-Forwarded-Proto $scheme; + + # websockets / SSE (if you ever use them) + proxy_set_header Upgrade $http_upgrade; + proxy_set_header Connection $connection_upgrade; - location /api { - proxy_pass http://paras-server:4009; - - # CORS headers - add_header Access-Control-Allow-Origin "*"; - add_header Access-Control-Allow-Methods "GET, POST, OPTIONS"; - add_header Access-Control-Allow-Headers "Content-Type, Authorization"; - - # Handle preflight requests (for POST requests) - if ($request_method = 'OPTIONS') { - add_header Access-Control-Allow-Origin "*"; - add_header Access-Control-Allow-Methods "GET, POST, OPTIONS"; - add_header Access-Control-Allow-Headers "Content-Type, Authorization"; - add_header Content-Length 0; - add_header Content-Type text/plain; - return 204; - } + # (optional) timeouts for long requests + proxy_read_timeout 300s; + proxy_send_timeout 300s; + + # CORS (only if you need cross-origin; if served via same origin, you can remove) + add_header Access-Control-Allow-Origin "*" always; + add_header Access-Control-Allow-Methods "GET, POST, PUT, PATCH, DELETE, OPTIONS" always; + add_header Access-Control-Allow-Headers "Content-Type, Authorization, X-Requested-With" always; + + # Preflight + if ($request_method = OPTIONS) { + return 204; } -} \ No newline at end of file + } + + # SPA fallback (client-side routing) + location / { + try_files $uri /index.html; + # Avoid caching index.html so new deploys show up + add_header Cache-Control "no-cache"; + } + + # Friendly error page + error_page 500 502 503 504 /50x.html; + location = /50x.html { + internal; + } +} + +# Globals +map $http_upgrade $connection_upgrade { + default upgrade; + '' close; +} diff --git a/app/src/client/package-lock.json b/app/src/client/package-lock.json index 87bd231..9cf73ca 100644 --- a/app/src/client/package-lock.json +++ b/app/src/client/package-lock.json @@ -1,12 +1,12 @@ { - "name": "paras", - "version": "1.0.0", + "name": "paras-webapp", + "version": "2.0.0", "lockfileVersion": 2, "requires": true, "packages": { "": { - "name": "paras", - "version": "1.0.0", + "name": "paras-webapp", + "version": "2.0.0", "dependencies": { "@emotion/react": "^11.13.3", "@emotion/styled": "^11.13.0", From 38565eb230e302019f3a6036890294d2a7386eab Mon Sep 17 00:00:00 2001 From: David Meijer Date: Thu, 4 Sep 2025 17:12:28 +0200 Subject: [PATCH 03/65] FIX: make sure new data files are included in build --- manifest.in | 2 ++ 1 file changed, 2 insertions(+) create mode 100644 manifest.in diff --git a/manifest.in b/manifest.in new file mode 100644 index 0000000..56ae63c --- /dev/null +++ b/manifest.in @@ -0,0 +1,2 @@ +recursive-include src/parasect/data *.txt *.tsv *.fasta *.hmm +recursive-include src/parasect/data/database_files *.tsv \ No newline at end of file From 14d648b617039a6be500bcee68c5711c7067788a Mon Sep 17 00:00:00 2001 From: David Meijer Date: Thu, 4 Sep 2025 17:12:39 +0200 Subject: [PATCH 04/65] FIX: make sure new data files are included in build --- setup.cfg | 1 + 1 file changed, 1 insertion(+) diff --git a/setup.cfg b/setup.cfg index 6eb846f..ed98617 100644 --- a/setup.cfg +++ b/setup.cfg @@ -65,6 +65,7 @@ parasect.data = *.hmm *.tsv *.fasta + database_files/*.tsv [options.extras_require] tests = From b91dff0720b9eefa9fea3332d1519180e7e45a01 Mon Sep 17 00:00:00 2001 From: David Meijer Date: Thu, 4 Sep 2025 23:07:12 +0200 Subject: [PATCH 05/65] ENH: don't push .DS_Store --- .gitignore | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/.gitignore b/.gitignore index 8564a47..3b36f98 100644 --- a/.gitignore +++ b/.gitignore @@ -162,4 +162,7 @@ cython_debug/ # do not push anythin in the condensed/out folder apart from .gitkeep condensed/out/* -!condensed/out/.gitkeep \ No newline at end of file +!condensed/out/.gitkeep + +# macOS +.DS_Store \ No newline at end of file From 2c10f7eb5e1a1b6daa25658f44fcb78164446818 Mon Sep 17 00:00:00 2001 From: David Meijer Date: Thu, 4 Sep 2025 23:07:24 +0200 Subject: [PATCH 06/65] UPD: add psutils --- app/server-requirements.txt | 1 + 1 file changed, 1 insertion(+) diff --git a/app/server-requirements.txt b/app/server-requirements.txt index 7a3c323..51f0de1 100644 --- a/app/server-requirements.txt +++ b/app/server-requirements.txt @@ -6,4 +6,5 @@ flask_sqlalchemy gunicorn joblib apscheduler +psutil git+https://github.com/BTheDragonMaster/parasect@webapp_dev_docker \ No newline at end of file From 5396836c792aa344c2f7cb04584c025596230042 Mon Sep 17 00:00:00 2001 From: David Meijer Date: Thu, 4 Sep 2025 23:07:34 +0200 Subject: [PATCH 07/65] ADD: logging --- app/src/server/routes/app.py | 18 +++++++++++++++++- 1 file changed, 17 insertions(+), 1 deletion(-) diff --git a/app/src/server/routes/app.py b/app/src/server/routes/app.py index 8f5d579..ca55e16 100644 --- a/app/src/server/routes/app.py +++ b/app/src/server/routes/app.py @@ -3,15 +3,31 @@ """Module for defining the Flask app.""" import atexit +import logging import os import time from apscheduler.schedulers.background import BackgroundScheduler from apscheduler.triggers.interval import IntervalTrigger -from flask import Flask +from flask import Flask, request + + +logging.basicConfig(level=os.getenv("LOG_LEVEL", "INFO")) app = Flask(__name__) + +@app.before_request +def _t0(): + request._t0 = time.time() + +@app.after_request +def _log(resp): + dt = (time.time() - getattr(request, "_t0", time.time())) * 1000 + app.logger.info("method=%s path=%s status=%s dt_ms=%.1f", request.method, request.path, resp.status_code, dt) + return resp + + app.config["JOB_RESULTS"] = dict() app.config["SMILES"] = dict() From 4acf74b9f84332f8afe1b25171331c4b12fa46ad Mon Sep 17 00:00:00 2001 From: David Meijer Date: Thu, 4 Sep 2025 23:10:03 +0200 Subject: [PATCH 08/65] ENH: add ModelSpec + MultiModelLoader for lazy mmp'd model loading for mitigating OOM on large RF --- app/src/server/routes/model_loader.py | 67 +++++++++++++++++++++++++++ app/src/server/routes/submit.py | 30 ++++++------ 2 files changed, 83 insertions(+), 14 deletions(-) create mode 100644 app/src/server/routes/model_loader.py diff --git a/app/src/server/routes/model_loader.py b/app/src/server/routes/model_loader.py new file mode 100644 index 0000000..f5b6970 --- /dev/null +++ b/app/src/server/routes/model_loader.py @@ -0,0 +1,67 @@ +import threading, logging +from dataclasses import dataclass +from typing import Callable, Dict, Optional, Any + + +try: + import psutil + _proc = psutil.Process() +except Exception: # psutil optional + _proc = None + + +# Prefer joblig for large sklearn models (supports mmap arrays) +try: + from joblib import load as joblib_load +except Exception: + joblib_load = None + + +@dataclass +class ModelSpec: + name: str + path: str + loader: Optional[Callable[[str], Any]] = None # custom loader + mmap: bool = True # if True and joblib available, mmap arrays (lower peak RAM) + + +class MultiModelLoader: + def __init__(self, specs: Dict[str, ModelSpec]): + self._specs = specs + self._models: Dict[str, Any] = {} + self._locks: Dict[str, threading.Lock] = {k: threading.Lock() for k in specs} + + def _rss(self) -> str: + """Return the resident set size (RSS) memory usage of the process.""" + if not _proc: + return "n/a" + return f"{_proc.memory_info().rss/1024/1024:.1f} MB" + + def _default_load(self, path: str, mmap: bool) -> Any: + # Try joblib with mmap first + if joblib_load: + mmap_mode = "r" if mmap else None + return joblib_load(path, mmap_mode=mmap_mode) + # Fallback to pickle + import pickle + with open(path, "rb") as fh: + return pickle.load(fh) + + def get(self, key: str): + if key in self._models: + return self._models[key] + if key not in self._specs: + raise KeyError(f"Unknown model key: {key}") + + spec = self._specs[key] + lock = self._locks[key] + + with lock: + if key in self._models: # double check + return self._models[key] + logging.info(f"Loading model '%s' from %s (rss=%s)", spec.name, spec.path, self._rss()) + loader = spec.loader or (lambda p: self._default_load(p, spec.mmap)) + model = loader(spec.path) + self._models[key] = model + logging.info(f"Loaded model '%s' from (rss=%s)", spec.name, self._rss()) + return model diff --git a/app/src/server/routes/submit.py b/app/src/server/routes/submit.py index a4b9ab7..7058703 100644 --- a/app/src/server/routes/submit.py +++ b/app/src/server/routes/submit.py @@ -18,6 +18,21 @@ from .app import app from .common import ResponseData, Status from .constants import MODEL_DIR, TEMP_DIR +from .model_loader import ModelSpec, MultiModelLoader + + +# Model registry +MODEL_PARAS_ALL_SUBSTRATES = os.path.join(MODEL_DIR, "all_substrates_model.paras") +MODEL_PARAS_COMMON_SUBSTRATES = os.path.join(MODEL_DIR, "model.paras") +MODEL_PARASECT = os.path.join(MODEL_DIR, "model.parasect") + + +loader = MultiModelLoader({ + "parasAllSubstrates": ModelSpec(name="PARAS (all substrates)", path=MODEL_PARAS_ALL_SUBSTRATES, mmap=True), + "parasCommonSubstrates": ModelSpec(name="PARAS (common substrates)", path=MODEL_PARAS_COMMON_SUBSTRATES, mmap=True), + "parasect": ModelSpec(name="PARASECT", path=MODEL_PARASECT, mmap=True) +}) + blueprint_submit_raw = Blueprint("submit_raw", __name__) blueprint_submit_quick = Blueprint("submit_quick", __name__) @@ -83,20 +98,7 @@ def run_prediction_raw(job_id: str, data: Dict[str, str]) -> None: # load model # return error if not successful try: - if selected_model == "parasAllSubstrates": - model = joblib.load(os.path.join(MODEL_DIR, "all_substrates_model.paras")) - model.set_params(n_jobs=1) - assert model is not None - elif selected_model == "parasCommonSubstrates": - model = joblib.load(os.path.join(MODEL_DIR, "model.paras")) - model.set_params(n_jobs=1) - assert model is not None - elif selected_model == "parasect": - model = joblib.load(os.path.join(MODEL_DIR, "model.parasect")) - model.set_params(n_jobs=1) - assert model is not None - else: - raise Exception("not successful loading model") + model = loader.get(selected_model) except Exception as e: msg = f"failed to load model: {str(e)}" raise Exception(msg) From f621ec3f6efae55cc34d0a95a946ee21b2ef31f7 Mon Sep 17 00:00:00 2001 From: David Meijer Date: Thu, 4 Sep 2025 23:17:29 +0200 Subject: [PATCH 09/65] ADD: health check --- app/src/server/routes/app.py | 7 +++++++ 1 file changed, 7 insertions(+) diff --git a/app/src/server/routes/app.py b/app/src/server/routes/app.py index ca55e16..0c9496e 100644 --- a/app/src/server/routes/app.py +++ b/app/src/server/routes/app.py @@ -17,10 +17,12 @@ app = Flask(__name__) + @app.before_request def _t0(): request._t0 = time.time() + @app.after_request def _log(resp): dt = (time.time() - getattr(request, "_t0", time.time())) * 1000 @@ -28,6 +30,11 @@ def _log(resp): return resp +@app.get("/health") +def health(): + return {"ok": True}, 200 + + app.config["JOB_RESULTS"] = dict() app.config["SMILES"] = dict() From b23bd361c3bd7e568a7bcabd9a4016fd0742cdee Mon Sep 17 00:00:00 2001 From: David Meijer Date: Thu, 4 Sep 2025 23:21:02 +0200 Subject: [PATCH 10/65] ENH: update deployment with more resource controls and health check --- app/Dockerfile.server | 11 ++++++++++- app/docker-compose.yml | 17 ++++++++++++++++- 2 files changed, 26 insertions(+), 2 deletions(-) diff --git a/app/Dockerfile.server b/app/Dockerfile.server index 5b28c80..dfe024e 100644 --- a/app/Dockerfile.server +++ b/app/Dockerfile.server @@ -31,6 +31,15 @@ COPY --chown=${USER_UID}:${USER_GID} ./src/server/ /app/ # Ensure temp dir exists and is writable RUN mkdir -p /app/temp && chown -R ${USER_UID}:${USER_GID} /app +# Runtime env: unbuffered logs, mmap for joblib, cap math threads +ENV PYTHONUNBUFFERED=1 \ + LOG_LEVEL=INFO \ + OMP_NUM_THREADS=1 \ + OPENBLAS_NUM_THREADS=1 \ + MKL_NUM_THREADS=1 \ + NUMEXPR_NUM_THREADS=1 \ + JOBLIB_MMAP_MODE=r + # Use the unprivileged user at runtime USER $USERNAME @@ -39,4 +48,4 @@ EXPOSE 4009 # Run everything inside the conda env without needing manual activation ENTRYPOINT ["conda", "run", "--no-capture-output", "-n", "web"] -CMD ["gunicorn", "-b", ":4009", "--timeout", "120", "api:app"] +CMD ["gunicorn", "-b", ":4009", "--worker-class", "gthread", "--workers", "1", "--threads", "4", "--preload", "--timeout", "120", "api:app"] diff --git a/app/docker-compose.yml b/app/docker-compose.yml index 5822c12..54e97e1 100644 --- a/app/docker-compose.yml +++ b/app/docker-compose.yml @@ -9,10 +9,25 @@ services: restart: always container_name: paras-server volumes: - - ./models:/app/models:rw + - ./models:/app/models:ro environment: - MODEL_DIR=/app/models + - LOG_LEVEL=INFO + # Also set in Dockerfile, can override here + - OMP_NUM_THREADS=1 + - OPENBLAS_NUM_THREADS=1 + - MKL_NUM_THREADS=1 + - NUMEXPR_NUM_THREADS=1 + - JOBLIB_MMAP_MODE=r networks: [paras-network] + healthcheck: + # Use base Python; no curl/wget dependency needed + test: [ "CMD", "/opt/conda/bin/python", "-c", + "import urllib.request,sys; urllib.request.urlopen('http://localhost:4009/health', timeout=2); sys.exit(0)" ] + interval: 10s + timeout: 3s + retries: 10 + start_period: 5s paras-client: build: From cd78bae0346b055b58045ecb9cb31223baf3405c Mon Sep 17 00:00:00 2001 From: David Meijer Date: Thu, 4 Sep 2025 23:41:38 +0200 Subject: [PATCH 11/65] FIX: use model loader everywhere; prevent fail on too many open files --- app/src/server/routes/data_annotation.py | 8 +++----- app/src/server/routes/model_loader.py | 11 +++++++++-- app/src/server/routes/submit.py | 4 +--- 3 files changed, 13 insertions(+), 10 deletions(-) diff --git a/app/src/server/routes/data_annotation.py b/app/src/server/routes/data_annotation.py index 4a63cf1..d780898 100644 --- a/app/src/server/routes/data_annotation.py +++ b/app/src/server/routes/data_annotation.py @@ -16,8 +16,9 @@ from .app import app from .common import ResponseData, Status -from .constants import MODEL_DIR, TEMP_DIR +from .constants import TEMP_DIR from .database import get_db +from .submit import loader blueprint_annotate_data = Blueprint("annotate_data", __name__) @@ -64,10 +65,7 @@ def run_prediction_protein(job_id: str, data: Dict[str, str]) -> None: # load model # return error if not successful try: - model = joblib.load(os.path.join(MODEL_DIR, "all_substrates_model.paras")) - model.set_params(n_jobs=1) - assert model is not None - + model = loader.get("parasAllSubstrates") except Exception as e: msg = f"failed to load model: {str(e)}" raise Exception(msg) diff --git a/app/src/server/routes/model_loader.py b/app/src/server/routes/model_loader.py index f5b6970..51ccea1 100644 --- a/app/src/server/routes/model_loader.py +++ b/app/src/server/routes/model_loader.py @@ -1,4 +1,4 @@ -import threading, logging +import threading, logging, errno from dataclasses import dataclass from typing import Callable, Dict, Optional, Any @@ -41,7 +41,14 @@ def _default_load(self, path: str, mmap: bool) -> Any: # Try joblib with mmap first if joblib_load: mmap_mode = "r" if mmap else None - return joblib_load(path, mmap_mode=mmap_mode) + try: + return joblib_load(path, mmap_mode=mmap_mode) + except OSError as e: + logging.warning("Joblib failed to load %s: %s", path, e) + if e.errno == errno.EMFILE: + logging.warning("Too many open files; retrying load without mmap: %s", path) + return joblib_load(path, mmap_mode=None) + raise # Fallback to pickle import pickle with open(path, "rb") as fh: diff --git a/app/src/server/routes/submit.py b/app/src/server/routes/submit.py index 7058703..ef04902 100644 --- a/app/src/server/routes/submit.py +++ b/app/src/server/routes/submit.py @@ -297,9 +297,7 @@ def run_prediction_signature(job_id: str, data: Dict[str, str]) -> None: # load model # return error if not successful try: - model = joblib.load(os.path.join(MODEL_DIR, "model.paras")) - model.set_params(n_jobs=1) - assert model is not None + model = loader.get("parasCommonSubstrates") except Exception as e: msg = f"failed to load model: {str(e)}" raise Exception(msg) From 1cfd21f6a18204f2b8431bf72685905017d0e9ee Mon Sep 17 00:00:00 2001 From: David Meijer Date: Thu, 4 Sep 2025 23:45:28 +0200 Subject: [PATCH 12/65] REF: not able to retrieve annotation submissions --- app/src/client/src/pages/annotation_editor.js | 16 ---------------- 1 file changed, 16 deletions(-) diff --git a/app/src/client/src/pages/annotation_editor.js b/app/src/client/src/pages/annotation_editor.js index f13e295..054b115 100644 --- a/app/src/client/src/pages/annotation_editor.js +++ b/app/src/client/src/pages/annotation_editor.js @@ -168,19 +168,7 @@ const AnnotationEditor = () => { Extracted adenylation domains - - - { - navigator.clipboard.writeText(jobId); - toast.success('Copied the job ID to clipboard!'); - }} - > - - - {`Job ID: ${jobId}`} - @@ -195,10 +183,6 @@ const AnnotationEditor = () => { - - - You can use the job ID to retrieve the results at a later time. All jobs are automatically deleted after 7 days. - + + + + - - - - - In total, {results.length} of the submitted proteins contain adenylation domains. The tiles below show the domains for each protein. You can scroll horizontally to view all proteins. - - - - Domains which already exist in the PARAS/PARASECT dataset are displayed in grey. New domains are displayed in yellow. - - - - - - - + {/* display results in a row, one item per protein */} + + {results.map((result, index) => ( + + ))} - - - {/* display results in a row, one item per protein */} - - {results.map((result, index) => ( - - ))} - - + {/* Dialogue modal */} + + + + + Submit annotations + + + + + + + + + + + + + + + ); }; diff --git a/app/src/client/src/pages/data_annotation.js b/app/src/client/src/pages/data_annotation.js index 61ee7dc..266a18f 100644 --- a/app/src/client/src/pages/data_annotation.js +++ b/app/src/client/src/pages/data_annotation.js @@ -1,30 +1,9 @@ import React, { useState, useEffect } from 'react'; import { toast } from 'react-toastify'; import { Box, Button, Divider, TextField, FormControl, FormLabel, RadioGroup, FormControlLabel, Radio, CircularProgress, Typography, Input } from '@mui/material'; -import { MdSettings } from 'react-icons/md'; const exampleFastaInput = '>dptA\nMDMQSQRLGVTAAQQSVWLAGQLADDHRLYHCAAYLSLTGSIDPRTLGTAVRRTLDETEALRTRFVPQDGELLQILEPGAGQLLLEADFSGDPDPERAAHDWMHAALAAPVRLDRAGTATHALLTLGPSRHLLYFGYHHIALDGYGALLHLRRLAHVYTALSNGDDPGPCPFGPLAGVLTEEAAYRDSDNHRRDGEFWTRSLAGADEAPGLSEREAGALAVPLRRTVELSGERTEKLAASAAATGARWSSLLVAATAAFVRRHAAADDTVIGLPVTARLTGPALRTPCMLANDVPLRLDARLDAPFAALLADTTRAVGTLARHQRFRGEELHRNLGGVGRTAGLARVTVNVLAYVDNIRFGDCRAVVHELSSGPVRDFHINSYGTPGTPDGVQLVFSGNPALYTATDLADHQERFLRFLDAVTADPDLPTGRHRLLSPGTRARLLDDSRGTERPVPRATLPELFAEQARRTPDAPAVQHDGTVLTYRDLHRSVERAAGRLAGLGLRTEDVVALALPKSAESVAILLGIQRAGAAYVPLDPTHPAERLARVLDDTRPRYLVTTGHIDGLSHPTPQLAAADLLREGGPEPAPGRPAPGNAAYIIQTSGSTGRPKGVVVTHEGLATLAADQIRRYRTGPDARVLQFISPGFDVFVSELSMTLLSGGCLVIPPDGLTGRHLADFLAAEAVTTTSLTPGALATMPATDLPHLRTLIVGGEVCPPEIFDQWGRGRDIVNAYGPTETTVEATAWHRDGATHGPVPLGRPTLNRRGYVLDPALEPVPDGTTGELYLAGEGLARGYVAAPGPTAERFVADPFGPPGSRMYRTGDLVRRRSGGMLEFVGRADGQVKLRGFRIELGEVQAALTALPGVRQAGVLIREDRPGDPRLVGYIVPAPGAEPDAGELRAALARTLPPHMVPWALVPLPALPLTSNGKLDRAALPVPAARAGGSGQRPVTPQEKTLCALFADVLGVTEVATDDVFFELGGHSLNGTRLLARIRTEFGTDLTLRDLFAFPTVAGLLPLLDDNGRQHTTPPLPPRPERLPLSHAQQRLWFLDQVEGPSPAYNIPTAVRLEGPLDIPALAVALQDVTNRHEPLRTLLAEDSEGPHQVILPPEAARPELTHSTVAPGDLAAALAEAARRPFDLAGEIPLKAHLFGCGPDDHTLLLLVHHTAGDGASVEVLVRDLAHAYGARRAGDAPHFEPLPLQYADHTLRRRHLLDDPSDSTQLDHWRDALAGLPEQLELPTDHTRPAVPTRRGEAIAFTVPEHTHHTLRAMAQAHGVTVFMVMQAALAALLSRHGAGHDIPLGTPVAGRSDDGTEDLVGFFVNTLVLRNDVSGDPTFAELVSRVRAANLDAYAYQDVPFERLVDVLKPERSLSWHPLFQIMIAYNGPATNDTADGSRFAGLTSRVHAVHTGMSKFDLSFFLTEHADGLGIDGALEFSTDLFTRITAERLVQRYLTVLEQAAGAPDRPISSYELLGDDERALLAQWNDTAHPTPPGTVLDLLESRAARTPDRPAVVENDHVLTYADLHTRANRLARHLITAHGVGPERLVAVALPRSAELLVALLAVLKTGAAYVPLDLTHPAERTAVVLDDCRPAVILTDAGAARELPRRDIPQLRLDEPEVHAAIAEQPGGPVTDRDRTCVTPVSGEHVAYVIYTSGSTGRPKGVAVEHRSLADFVRYSVTAYPGAFDVTLLHSPVTFDLTVTSLFPPLVVGGAIHVADLTEACPPSLAAAGGPTFVKATPSHLPLLTHEATWAASAKVLLVGGEQLLGRELDKWRAGSPEAVVFNDYGPTEATVNCVDFRIDPGQPIGAGPVAIGRPLRNTRVFVLDGGLRAVPVGVVGELHVAGEGLARGYLGQPGLTAERFVACPFGDAGERMYRTGDLVRWRADGMLEFVGRVDDQVKVRGFRIELGEVEAAVAACPGVDRSVVVVREDRPGDRRLVAYVTAAGDEAEGLAPLIVETAAGRLPGYMVPSAVVVLDEIPLTPNGKVDRAALPAPRVAPAAEFRVTGSPREEALCALFAEVLGVERVGVDDGFFDLGGDSILSIQLVARARRAGLEVSVRDVFEHRTVRALAGVVRESGGVAAAVVDSGVGAVERWPVVEWLAERGGGGLGGAVRAFNQSVVVATPAGITWDELRTVLDAVRERHDAWRLRVVDSGDGAWSLRVDAPAPGGEPDWITRHGMASADLEEQVNAVRAAAVEARSRLDPLTGRMVRAVWLDRGPDRRGVLVLVAHHLVVDGVSWRIVLGDLGEAWTQARAGGHVRLDTVGTSLRGWAAALAEQGRHGARATEANLWAQMVHGSDPLVGPRAVDPSVDVFGVVESVGSRASVGVSRALLTEVPSVLGVGVQEVLLAAFGLAVTRWRGRGGSVVVDVEGHGRNEDAVPGADLSRTVGWFTSIYPVRLPLEPAAWDEIRAGGPAVGRTVREIKECLRTLPDQGLGYGILRYLDPENGPALAQHPTPHFGFNYLGRVSVSADAASLDEGDAHADGLGGLVGGRAAADSDEEQWADWVPVSGPFAVGAGQDPVLPVAHAVEFNAITLDTPDGPRLSVTWSWPTTLLSESRIRELARFWDEALEGLVAHARRPDAGGLTPSDLPLVALDHAELEALQADVTGGVHDILPVSPLQEGLLFHSSFAADGVDVYVGQLTFDLTGPVDADHLHAVVESLVTRHDVLRTGYRQAQSGEWIAVVARQVHTPWQYIHTLDTDADTLTNDERWRPFDMTQGPLARFTLARINDTHFRFIVTYHHVILDGWSVAVLIRELFTTYRDTALGRRPEVPYSPPRRDFMAWLAERDQTAAGQAWRSALAGLAEPTVLALGTEGSGVIPEVLEEEISEELTSELVAWARGRGVTVASVVQAAWALVLGRLVGRDDVVFGLTVSGRPAEVAGVEDMVGLFVNTIPLRARMDPAESLGAFVERLQREQTELLEHQHVRLAEVQRWAGHKELFDVGMVFENYPMDSLLQDSLFHGSGLQIDGIQGADATHFALNLAVVPLPAMRFRLGYRPDVFDAGRVRELWGWIVRALECVVCERDVPVSGVDVLGAGERETLLGWGAGAEPGVRALPGAGAGAGAGLVGLFEERVRTDPDAVAVRGAGVEWSYAELNARANAVARWLIGRGVGPERGVGVVMDRGPDVVAMLLAVAKSGGFYLPVDPQWPTERIDWVLADAGIDLAVVGENLAAAVEAVRDCEVVDYAQIARETRLNEQAATDAGDVTDGERVSALLSGHPLYVIYTSGSTGLPKGVVVTHASVGAYLRRGRNAYRGAADGLGHVHSSLAFDLTVTVLFTPLVSGGCVTLGDLDDTANGLGATFLKATPSHLPLLGQLDRVLAPDATLLLGGEALTAGALHHWRTHHPHTTVINAYGPTELTVNCAEYRIPPGHCLPDGPVPIGRPFTGHHLFVLDPALRLTPPDTIGELYVAGDGLARGYLGRPDLTAERFVACPFRSPGERMYRTGDLARWRSDGTLEFIGRADDQVKIRGFRIELGEVEAAVAAHPHVARAIAVVREDRPGDQRLVAYVTGSDPSGLSSAVTDTVAGRLPAYMVPSAVVVLDQIPLTPNGKVDRAALPAPGTASGTTSRAPGTAREEILCTLFADVLGLDQVGVDEDFFDLGGHSLLATRLTSRIRSALGIDLGVRALFKAPTVGRLDQLLQQQTTSLRAPLVARERTGCEPLSFAQQRLWFLHQLEGPNAAYNIPMALRLTGRLDLTALEAALTDVIARHESLRTVIAQDDSGGVWQNILPTDDTRTHLTLDTMPVDAHTLQNRVDEAARHPFDLTTEIPLRATVFRVTDDEHVLLLVLHHIAGDGWSMAPLAHDLSAAYTVRLEHHAPQLPALAVQYADYAAWQRDVLGTENNTSSQLSTQLDYWYSKLEGLPAELTLPTSRVRPAVASHACDRVEFTVPHDVHQGLTALARTQGATVFMVVQAALAALLSRLGAGTDIPIGTPIAGRTDQAMENLIGLFVNTLVLRTDVSGDPTFAELLARVRTTALDAYAHQDIPFERLVEAINPERSLTRHPLFQVMLAFNNTDRRSALDALDAMPGLHARPADVLAVTSPYDLAFSFVETPGSTEMPGILDYATDLFDRSTAEAMTERLVRLLAEIARRPELSVGDIGILSADEVKALSPEAPPAAEELHTSTLPELFEEQVAARGHAVAVVCEGEELSYKELNARANRLARVLMERGAGPERFVGVALPRGLDLIVALLAVTKTGAAYVPLDPEYPTDRLAYMVTDANPTAVVTSTDVHIPLIAPRIELDDEAIRTELAAAPDTAPCVGSGPAHPAYVIYTSGSTGRPKGVVISHANVVRLFTACSDSFDFGPDHVWTLFHSYAFDFSVWEIWGALLHGGRLVVVPFEVTRSPAEFLALLAEQQVTLLSQTPSAFHQLTEAARQEPARCAGLALRHVVFGGEALDPSRLRDWFDLPLGSRPTLVNMYGITETTVHVTVLPLEDRATSLSGSPIGRPLADLQVYVLDERLRPVPPGTVGEMYVAGAGLARGYLGRPALTAERFVADPNSRSGGRLYRTGDLAKVRPDGGLEYVGRGDRQVKIRGFRIELGEIEAALVTHAGVVQAVVLVRDEQTDDQRLVAHVVPALPHRAPTLAELHEHLAATLPAYMVPSAYRTLDELPLTANGKLDRAALAGQWQGGTRTRRLPRTPQEEILCELFADVLRLPAAGADDDFFALGGHSLLATRLLSAVRGTLGVELGIRDLFAAPTPAGLATVLAASGTALPPVTRIDRRPERLPLSFAQRRLWFLSKLEGPSATYNIPVAVRLTGALDVPALRAALGDVTARHESLRTVFPDDGGEPRQLVLPHAEPPFLTHEVTVGEVAEQAASATGYAFDITSDTPLRATLLRVSPEEHVLVVVIHHIAGDGWSMGPLVRDLVTAYRARTRGDAPEYTPLPVQYADYALWQHAVAGDEDAPDGRTARRLGYWREMLAGLPEEHTLPADRPRPVRSSHRGGRVRFELPAGVHRSLLAVARDRRATLFMVVQAALAGLLSRLGAGDDIPIGTPVAGRGDEALDDVVGFFVNTLVLRTNLAGDPSFADLVDRVRTADLDAFAHQDVPFERLVEALAPRRSLARHPLFQIWYTLTNADQDITGQALNALPGLTGDEYPLGASAAKFDLSFTFTEHRTPDGDAAGLSVLLDYSSDLYDHGTAAALGHRLTGFFAALAADPTAPLGTVPLLTDDERDRILGDWGSGTHTPLPPRSVAEQIVRRAALDPDAVAVITAEEELSYRELERLSGETARLLADRGIGRESLVAVALPRTAGLVTTLLGVLRTGAAYLPLDTGYPAERLAHVLSDARPDLVLTHAGLAGRLPAGLAPTVLVDEPQPPAAAAPAVPTSPSGDHLAYVIHTSGSTGRPKGVAIAESSLRAFLADAVRRHDLTPHDRLLAVTTVGFDIAGLELFAPLLAGAAIVLADEDAVRDPASITSLCARHHVTVVQATPSWWRAMLDGAPADAAARLEHVRILVGGEPLPADLARVLTATGAAVTNVYGPTEATIWATAAPLTAGDDRTPGIGTPLDNWRVHILDAALGPVPPGVPGEIHIAGSGLARGYLRRPDLTAERFVANPFAPGERMYRTGDLGRFRPDGTLEHLGRVDDQVKVRGFRIELGDVEAALARHPDVGRAAAAVRPDHRGQGRLVAYVVPRPGTRGPDAGELRETVRELLPDYMVPSAQVTLTTLPHTPNGKLDRAALPAPVFGTPAGRAPATREEKILAGLFADILGLPDVGADSGFFDLGGDSVLSIQLVSRARREGLHITVRDVFEHGTVGALAAAALPAPADDADDTVPGTDVLPSISDDEFEEFELELGLEGEEEQW'; -/** - * Component to annotate data. - * - * @param {Object} props - The props of the component. - * @param {string} props.imageSrc - The path to the image. - * @param {string} props.label - The label for the radio button. - * @returns {React.ReactElement} - The data annotation component. - */ -const RadioLabel = ({ imageSrc, label }) => ( - - - {label} - -); - /** * Component to annotate data. @@ -229,7 +208,6 @@ const DataAnnotation = () => { - ); }; diff --git a/app/src/server/run_server.sh b/app/src/server/run_server.sh index b2fdc70..2c3dd74 100644 --- a/app/src/server/run_server.sh +++ b/app/src/server/run_server.sh @@ -1,5 +1,10 @@ #!/bin/bash +# Load environment variables from .env in project root +set -a +source "$(dirname "$0")/../../.env" +set +a + # Set environment variables export FLASK_APP=api.py export FLASK_ENV=development From 82a6de5984f57a06dc6bc3ed9e6ba1b14edbf5ee Mon Sep 17 00:00:00 2001 From: David Meijer Date: Fri, 5 Sep 2025 14:36:21 +0200 Subject: [PATCH 18/65] WIP: submitting annotations to github --- src/parasect/core/github.py | 7 +++++-- 1 file changed, 5 insertions(+), 2 deletions(-) diff --git a/src/parasect/core/github.py b/src/parasect/core/github.py index 5c3d479..1b6ba90 100644 --- a/src/parasect/core/github.py +++ b/src/parasect/core/github.py @@ -96,7 +96,11 @@ def submit_github_issue_protein(protein_entry, domains, new_substrates, annotati issue = {"title": title, "body": body} response = requests.post(url, json=issue, headers=headers) - print(response.status_code) + + # evaluate response code and throw error if not good + if response.status_code != 201: + raise ValueError(f"Failed to create GitHub issue: {response.text}") + return response.json() @@ -108,7 +112,6 @@ def submit_github_issues(session: Session, protein_to_entry: dict[str, dict[str, :param protein_to_entry: dictionary of protein names as keys and protein and domain annotations as (nested) values :type protein_to_entry: dict[str, dict[str, Any]] """ - for protein_name, protein_info in protein_to_entry.items(): protein_entry = ProteinEntry(protein_name, protein_info["sequence"]) From ceee04f815ff89e116803767d17006762b43a54e Mon Sep 17 00:00:00 2001 From: "Terlouw, Barbara" Date: Fri, 5 Sep 2025 15:33:36 +0200 Subject: [PATCH 19/65] Add command line interface for PARAS --- setup.cfg | 3 +- src/parasect/api.py | 61 +-------- src/parasect/cli_paras.py | 110 ++++++++++++++++ src/parasect/{cli.py => cli_parasect.py} | 0 src/parasect/core/featurisation.py | 5 +- src/parasect/core/fetch_from_genbank.py | 25 ---- src/parasect/core/genbank.py | 78 +++++++++++ src/parasect/core/helpers.py | 122 ++++++++++++++++++ src/parasect/core/parasect_result.py | 86 ++++++++++++ src/parasect/core/writers.py | 49 +++++++ src/parasect/database/add_user_submissions.py | 3 +- 11 files changed, 454 insertions(+), 88 deletions(-) create mode 100644 src/parasect/cli_paras.py rename src/parasect/{cli.py => cli_parasect.py} (100%) delete mode 100644 src/parasect/core/fetch_from_genbank.py create mode 100644 src/parasect/core/genbank.py create mode 100644 src/parasect/core/helpers.py create mode 100644 src/parasect/core/parasect_result.py create mode 100644 src/parasect/core/writers.py diff --git a/setup.cfg b/setup.cfg index 6eb846f..e3360a6 100644 --- a/setup.cfg +++ b/setup.cfg @@ -74,7 +74,8 @@ tests = [options.entry_points] console_scripts = - parasect = parasect.cli:main + parasect = parasect.cli_parasect:main + paras = parasect.cli_paras:main ###################### # Doc8 Configuration # diff --git a/src/parasect/api.py b/src/parasect/api.py index 4aa6cd2..6421c49 100644 --- a/src/parasect/api.py +++ b/src/parasect/api.py @@ -16,8 +16,9 @@ data_from_substrate_names, parse_substrate_list, ) -from parasect.core.fetch_from_genbank import fetch_from_genbank +from parasect.core.genbank import fetch_from_genbank from parasect.core.tabular import Tabular +from parasect.core.parasect_result import Result def sort_results(results: List["AnnotationResult"]) -> List["ProteinResult"]: @@ -85,64 +86,6 @@ def to_json(self): ) -class Result: - """Result class.""" - - def __init__( - self, - domain: AdenylationDomain, - predictions: List[float], - prediction_labels: List[str], - prediction_smiles: List[str], - ) -> None: - """Initialise the Result class. - - :param domain: Adenylation domain. - :type domain: AdenylationDomain - :param predictions: Predictions. - :type predictions: List[float] - :param prediction_labels: Prediction labels. - :type prediction_labels: List[str] - :param prediction_smiles: Prediction SMILES. - :type prediction_smiles: List[str] - """ - self.domain = domain - self._predictions = predictions - self._prediction_labels = prediction_labels - self._prediction_smiles = prediction_smiles - - def sort(self): - pred_label_smiles = list(zip(self._predictions, self._prediction_labels, self._prediction_smiles)) - pred_label_smiles.sort(key=lambda x: x[0], reverse=True) - self._predictions = [data[0] for data in pred_label_smiles] - self._prediction_labels = [data[1] for data in pred_label_smiles] - self._prediction_smiles = [data[2] for data in pred_label_smiles] - - def to_json(self) -> Dict[str, Union[str, int, List[Dict[str, Union[str, float]]]]]: - """Return the Result as a JSON serialisable dictionary. - - :return: JSON serialisable dictionary. - :rtype: Dict[str, Union[str, List[(float, str)]] - """ - return dict( - domain_name=self.domain.protein_name, - domain_nr=self.domain.domain_nr, - domain_start=self.domain.start, - domain_end=self.domain.end, - domain_sequence=self.domain.sequence, - domain_signature=self.domain.signature, - domain_extended_signature=self.domain.extended_signature, - predictions=[ - dict(substrate_name=sub_name, substrate_smiles=sub_smiles, probability=prob) - for sub_name, sub_smiles, prob in zip( - self._prediction_labels, - self._prediction_smiles, - self._predictions, - ) - ], - ) - - def run_paras( selected_input: str, selected_input_type: str, diff --git a/src/parasect/cli_paras.py b/src/parasect/cli_paras.py new file mode 100644 index 0000000..9c6acbb --- /dev/null +++ b/src/parasect/cli_paras.py @@ -0,0 +1,110 @@ +# -*- coding: utf-8 -*- + +"""CLI for PARASECT.""" + +import os +import argparse +import logging +from joblib import load + +from parasect.core.constants import SEPARATOR_1, SEPARATOR_2, SEPARATOR_3 +from parasect.api import run_paras +from parasect.core.helpers import download_and_unpack_or_fetch +from parasect.core.writers import write_fasta_file, write_results + + +def cli() -> argparse.Namespace: + """CLI for PARAS. + + :return: CLI arguments + :rtype: argparse.Namespace + """ + + parser = argparse.ArgumentParser() + + parser.add_argument('-i', "--input", type=str, required=True, help="Path to input fasta or gbk file.") + parser.add_argument('-f', "--file_type", type=str, default='fasta', + help="Input file type. Must be 'fasta' or 'gbk'.") + parser.add_argument('-o', "--output", type=str, required=True, help="Path to output directory.") + parser.add_argument('-j', "--job_name", type=str, default="run_1", + help="Job name") + parser.add_argument('-n', "--number_predictions", type=int, default=3, help="Number of top predictions to report.") + parser.add_argument('-t', "--temp", type=str, default=None, help="Temp dir. If not given, create temp folder in output dir") + parser.add_argument('-p', "--profile_alignment", action='store_true', + help="Use profile alignment instead of HMM for active site extraction") + parser.add_argument('-save_extended', action='store_true', + help="Save extended 34 amino acid signatures to file.") + parser.add_argument('-save_signatures', action='store_true', + help="Save short 10 amino acid signatures to file ('Stachelhaus code')") + parser.add_argument('-save_domains', action='store_true', + help="Save full a domain sequences to file ('Stachelhaus code')") + parser.add_argument('-all_substrates', action='store_true', + help="Use classifier that was trained on all substrates") + parser.add_argument('-s1', type=str, default=SEPARATOR_1, help="Symbol used as separator") + parser.add_argument('-s2', type=str, default=SEPARATOR_2, help="Symbol used as separator") + parser.add_argument('-s3', type=str, default=SEPARATOR_3, help="Symbol used as separator") + + args = parser.parse_args() + assert args.file_type.upper() in ["FASTA", "GBK"] + + return args + + +def main() -> None: + """Run CLI for PARASECT.""" + args = cli() + logger = logging.getLogger(__name__) + logging.basicConfig(level="INFO") + + if not os.path.exists(args.output): + os.mkdir(args.output) + + if args.temp is None: + temp_dir = os.path.join(args.output, "temp") + if not os.path.exists(temp_dir): + os.mkdir(temp_dir) + + else: + temp_dir = args.temp + + if args.all_substrates: + model_path = download_and_unpack_or_fetch(r"https://zenodo.org/records/13165500/files/all_substrates_model.paras?download=1", + temp_dir, logger) + + else: + model_path = download_and_unpack_or_fetch(r"https://zenodo.org/records/13165500/files/model.paras?download=1", + temp_dir, logger) + + model = load(model_path) + + with open(args.input, 'r') as input_file: + protein_data = input_file.read() + + results = run_paras(protein_data, args.file_type, temp_dir, model, args.profile_alignment) + + id_to_sig = {} + id_to_ext = {} + id_to_seq = {} + + for result in results: + domain_header = result.get_domain_header(args.s1, args.s2, args.s3) + if args.save_signatures: + id_to_sig[domain_header] = result.to_json()['domain_signature'] + if args.save_extended: + id_to_ext[domain_header] = result.to_json()['domain_extended_signature'] + if args.save_domains: + id_to_seq[domain_header] = result.to_json()['domain_sequence'] + + if args.save_signatures: + write_fasta_file(id_to_sig, os.path.join(args.output, f"{args.job_name}_signatures.fasta")) + if args.save_extended: + write_fasta_file(id_to_ext, os.path.join(args.output, f"{args.job_name}_extended_signatures.fasta")) + if args.save_domains: + write_fasta_file(id_to_seq, os.path.join(args.output, f"{args.job_name}_sequences.fasta")) + + results_out = os.path.join(args.output, f"{args.job_name}_paras_results.txt") + write_results(results, results_out, args.number_predictions) + + +if __name__ == "__main__": + main() diff --git a/src/parasect/cli.py b/src/parasect/cli_parasect.py similarity index 100% rename from src/parasect/cli.py rename to src/parasect/cli_parasect.py diff --git a/src/parasect/core/featurisation.py b/src/parasect/core/featurisation.py index f6564ac..16ace31 100644 --- a/src/parasect/core/featurisation.py +++ b/src/parasect/core/featurisation.py @@ -11,7 +11,8 @@ from parasect.core.constants import HMM2_FILE, HMM3_FILE, PROPERTIES from parasect.core.domain import AdenylationDomain from parasect.core.hmmer import parse_hmm_results, rename_sequences, reverse_renaming, run_hmmpfam2, run_hmmscan -from parasect.core.parsing import parse_fasta_file, parse_genbank_file +from parasect.core.parsing import parse_fasta_file +from parasect.core.genbank import genbank_to_fasta def get_domain_features(amino_acid_sequence: str) -> List[float]: @@ -453,7 +454,7 @@ def get_domains( if file_type == "gbk": # parse genbank file original_fasta = os.path.join(path_temp_dir, "proteins_from_genbank.fasta") - parse_genbank_file( + genbank_to_fasta( path_in=path_in, path_out=original_fasta ) # creates a fasta file at path_out mapping_file, renamed_fasta_file = rename_sequences( diff --git a/src/parasect/core/fetch_from_genbank.py b/src/parasect/core/fetch_from_genbank.py deleted file mode 100644 index 32d1ccc..0000000 --- a/src/parasect/core/fetch_from_genbank.py +++ /dev/null @@ -1,25 +0,0 @@ -# -*- coding: utf-8 -*- - -"""Module for handling HMMER requests.""" - - -import subprocess -from typing import Dict, List, Tuple - -from ncbi_acc_download.errors import DownloadError - - -def fetch_from_genbank(protein_accessions: List[str], fasta_out: str) -> None: - """Run hmmpfam2 on the given HMM database and fasta file. - - :param protein_accession: NCBI accession of protein sequence. - :type protein_accession: str - :param fasta_out: path to output fasta file - :type fasta_out: str - """ - - command = ["ncbi-acc-download", "--format", "fasta", '--molecule', 'protein', '--out', fasta_out] + protein_accessions - try: - subprocess.check_call(command) - except subprocess.CalledProcessError: - raise DownloadError("Could not find one or more NCBI accessions") diff --git a/src/parasect/core/genbank.py b/src/parasect/core/genbank.py new file mode 100644 index 0000000..66b4f5a --- /dev/null +++ b/src/parasect/core/genbank.py @@ -0,0 +1,78 @@ +# -*- coding: utf-8 -*- + +"""Module for handling HMMER requests.""" + + +import subprocess +from typing import List +import os +import itertools +from Bio import SeqIO + +from ncbi_acc_download.errors import DownloadError + +from parasect.core.writers import write_fasta_file + + +def genbank_to_fasta(path_in: str, path_out: str) -> None: + """Parse protein sequences from a GenBank file and writes them to a fasta file. + + :param path_in: Path to input GenBank file. + :type path_in: str + :param path_out: Path to output fasta file. + :type path_out: str + :raises FileNotFoundError: If the file at the specified path does not exist. + """ + # check if the file exists + if not os.path.exists(path_in): + raise FileNotFoundError(f"File not found: {path_in}") + + # initialize a counter for generating gene IDs + counter = itertools.count() + + # initialize a dictionary to store the fasta sequences + fasta_dict = {} + + # parse the GenBank file + for record in SeqIO.parse(path_in, "genbank"): + for feature in record.features: + + # check if the feature is a coding sequence (CDS) + if feature.type == "CDS": + + # check if the feature has a translation + if "translation" in feature.qualifiers: + sequence = feature.qualifiers["translation"] + + # check if the feature has a protein ID, gene ID, or locus tag + # to use as the sequence ID. If not, generate a gene ID + if "protein_id" in feature.qualifiers: + seq_id = feature.qualifiers["protein_id"][0] + elif "gene_id" in feature.qualifiers: + seq_id = feature.qualifiers["gene_id"][0] + elif "locus_tag" in feature.qualifiers: + seq_id = feature.qualifiers["locus_tag"][0] + else: + seq_id = f"gene_{next(counter)}" + + # add the sequence to the dictionary + fasta_dict[seq_id] = sequence + + # write the fasta sequences to a file + write_fasta_file(fasta_dict=fasta_dict, path_out=path_out) + + +def fetch_from_genbank(protein_accessions: List[str], fasta_out: str) -> None: + """Run hmmpfam2 on the given HMM database and fasta file. + + :param protein_accession: NCBI accession of protein sequence. + :type protein_accession: str + :param fasta_out: path to output fasta file + :type fasta_out: str + """ + + command = ["ncbi-acc-download", "--format", "fasta", '--molecule', 'protein', '--out', fasta_out] + protein_accessions + try: + subprocess.check_call(command) + except subprocess.CalledProcessError: + raise DownloadError("Could not find one or more NCBI accessions") diff --git a/src/parasect/core/helpers.py b/src/parasect/core/helpers.py new file mode 100644 index 0000000..8dd5899 --- /dev/null +++ b/src/parasect/core/helpers.py @@ -0,0 +1,122 @@ +import tarfile +import logging +from urllib.parse import urlsplit +from urllib.request import urlopen, Request +from pathlib import Path + + +def download_and_unpack_or_fetch( + url: str, + dest_dir: str, + logger: logging.Logger +) -> str: + """ + Download from `url` into `dest_dir` (creating it if needed). + + - Archives (.tar.gz/.tgz): + • If already downloaded & unpacked, returns existing unpacked path. + • Otherwise downloads & extracts, then returns unpacked folder path. + - Plain files: + • If already downloaded, returns existing file path. + • Otherwise downloads it, then returns the file path. + + Logs each step and shows download progress via the given logger. + + :param url: HTTP(S) URL of the file or archive to download. + :param dest_dir: Directory to save the downloaded file or unpacked archive. + :param logger: Logger for status/progress messages. + :return: Absolute path to the downloaded file or unpacked archive. + """ + dest = Path(dest_dir).expanduser().absolute() + logger.info(f"Using destination directory: {dest}") + dest.mkdir(parents=True, exist_ok=True) + + filename = Path(urlsplit(url).path).name + local_path = dest / filename + logger.info(f"Local path will be: {local_path}") + + def _download(): + req = Request(url, headers={'User-Agent': 'Python urllib'}) + with urlopen(req) as resp, open(local_path, 'wb') as out: + total_size = int(resp.getheader('Content-Length') or 0) + if total_size: + logger.info(f"Starting download of {filename} ({total_size} bytes)") + next_pct = 10 + else: + logger.info(f"Starting download of {filename} (size unknown)") + threshold = 1 * 1024 * 1024 # 1 MiB + next_bytes = threshold + + downloaded = 0 + chunk_size = 8192 + + while True: + chunk = resp.read(chunk_size) + if not chunk: + break + out.write(chunk) + downloaded += len(chunk) + + if total_size: + pct = downloaded * 100 / total_size + if pct >= next_pct: + logger.info(f"Downloaded {downloaded}/{total_size} bytes ({pct:.0f}%)") + next_pct += 10 + else: + if downloaded >= next_bytes: + logger.info(f"Downloaded {downloaded} bytes") + next_bytes += threshold + + logger.info("Download complete") + + is_tar = filename.lower().endswith(('.tar.gz', '.tgz')) + + if is_tar: + logger.info(f"Detected archive format for {filename}") + + def _get_roots(tar_path): + with tarfile.open(tar_path, 'r:gz') as tar: + return {Path(m.name).parts[0] for m in tar.getmembers() if m.name.strip()} + + # If archive exists, see if its contents are already unpacked + if local_path.exists(): + logger.info(f"Archive already exists at {local_path}, checking extraction") + try: + roots = _get_roots(local_path) + if len(roots) == 1: + candidate = dest / roots.pop() + if candidate.exists(): + logger.info(f"Found existing extracted folder {candidate}, skipping.") + return str(candidate) + else: + others = [p for p in dest.iterdir() if p != local_path] + if others: + logger.info(f"Found already-extracted contents in {dest}, skipping.") + return str(dest) + except tarfile.TarError: + logger.warning(f"Archive at {local_path} seems corrupt. Re-downloading.") + + # Download & extract + _download() + logger.info(f"Extracting {local_path} to {dest}") + with tarfile.open(local_path, 'r:gz') as tar: + roots = {Path(m.name).parts[0] for m in tar.getmembers() if m.name.strip()} + tar.extractall(path=dest) + + if len(roots) == 1: + unpacked = dest / roots.pop() + logger.info(f"Extraction complete: single folder {unpacked}") + return str(unpacked) + else: + logger.info(f"Extraction complete: multiple items, returning {dest}") + return str(dest) + + else: + # Plain file + logger.info(f"Detected single file for {filename}") + if not local_path.exists(): + logger.info(f"{local_path} not found locally; downloading.") + _download() + else: + logger.info(f"File already exists at {local_path}, skipping download.") + return str(local_path) diff --git a/src/parasect/core/parasect_result.py b/src/parasect/core/parasect_result.py new file mode 100644 index 0000000..e36dcff --- /dev/null +++ b/src/parasect/core/parasect_result.py @@ -0,0 +1,86 @@ +from typing import Union + +from parasect.core.domain import AdenylationDomain +from parasect.core.constants import SEPARATOR_1, SEPARATOR_2, SEPARATOR_3 + + +class Result: + """Result class.""" + + def __init__( + self, + domain: AdenylationDomain, + predictions: list[float], + prediction_labels: list[str], + prediction_smiles: list[str], + ) -> None: + """Initialise the Result class. + + :param domain: Adenylation domain. + :type domain: AdenylationDomain + :param predictions: Predictions. + :type predictions: List[float] + :param prediction_labels: Prediction labels. + :type prediction_labels: List[str] + :param prediction_smiles: Prediction SMILES. + :type prediction_smiles: List[str] + """ + self.domain = domain + self._predictions = predictions + self._prediction_labels = prediction_labels + self._prediction_smiles = prediction_smiles + + @property + def predictions(self): + return self._predictions + + @property + def prediction_labels(self): + return self._prediction_labels + + def sort(self): + pred_label_smiles = list(zip(self._predictions, self._prediction_labels, self._prediction_smiles)) + pred_label_smiles.sort(key=lambda x: x[0], reverse=True) + self._predictions = [data[0] for data in pred_label_smiles] + self._prediction_labels = [data[1] for data in pred_label_smiles] + self._prediction_smiles = [data[2] for data in pred_label_smiles] + + def get_domain_header(self, separator_1: str = SEPARATOR_1, separator_2: str = SEPARATOR_2, + separator_3: str = SEPARATOR_3) -> str: + """Get domain header for domain + + :param separator_1: Separator between header fields + :type separator_1: str + :param separator_2: Separator between 'domain' string and domain number + :type separator_2: str + :param separator_3: Separator between domain start and end coordinates + :type separator_3: str + :return: domain header + :rtype: str + """ + domain_header = f"{self.domain.protein_name}{separator_1}domain{separator_2}{self.domain.domain_nr}{separator_1}{self.domain.start}{separator_3}{self.domain.end}" + return domain_header + + def to_json(self) -> dict[str, Union[str, int, list[dict[str, Union[str, float]]]]]: + """Return the Result as a JSON serialisable dictionary. + + :return: JSON serialisable dictionary. + :rtype: Dict[str, Union[str, List[(float, str)]] + """ + return dict( + domain_name=self.domain.protein_name, + domain_nr=self.domain.domain_nr, + domain_start=self.domain.start, + domain_end=self.domain.end, + domain_sequence=self.domain.sequence, + domain_signature=self.domain.signature, + domain_extended_signature=self.domain.extended_signature, + predictions=[ + dict(substrate_name=sub_name, substrate_smiles=sub_smiles, probability=prob) + for sub_name, sub_smiles, prob in zip( + self._prediction_labels, + self._prediction_smiles, + self._predictions, + ) + ], + ) diff --git a/src/parasect/core/writers.py b/src/parasect/core/writers.py new file mode 100644 index 0000000..0842fce --- /dev/null +++ b/src/parasect/core/writers.py @@ -0,0 +1,49 @@ +from parasect.core.parasect_result import Result + + +def write_results(results: list[Result], out_file: str, number_predictions: int) -> None: + """Write PARAS results to file + + :param results: list of PARAS results + :type results: list[Result] + :param out_file: path to output file + :type out_file: str + :param number_predictions: number of predictions to report + :type number_predictions: int + """ + + if number_predictions > len(results[0].predictions): + raise ValueError(f"Cannot report top {number_predictions}; only {len(results[0].predictions)} substrates in model") + + with open(out_file, 'w') as out: + out.write("domain_id") + for i in range(number_predictions): + out.write(f"\tprediction_{i + 1}\tconfidence_prediction_{i + 1}") + + out.write('\n') + + for result in results: + result.sort() + out.write(result.get_domain_header()) + for i in range(number_predictions): + out.write(f"\t{result.prediction_labels[i]}\t{result.predictions[i]}") + + out.write('\n') + + +def write_fasta_file(fasta_dict: dict[str, str], path_out: str) -> None: + """Write a dictionary of fasta sequences to a file. + + :param fasta_dict: Dictionary of fasta sequences, where the key is the sequence + header and the value is the sequence. + :type fasta_dict: Dict[str, str] + :param path_out: Path to output fasta file. + :type path_out: str + """ + sorted_ids = sorted(fasta_dict.keys()) + with open(path_out, "w") as fo: + + # iterate over the dictionary items + for header in sorted_ids: + sequence = fasta_dict[header] + fo.write(f">{header}\n{sequence}\n") \ No newline at end of file diff --git a/src/parasect/database/add_user_submissions.py b/src/parasect/database/add_user_submissions.py index cb11aee..74794de 100644 --- a/src/parasect/database/add_user_submissions.py +++ b/src/parasect/database/add_user_submissions.py @@ -5,7 +5,8 @@ from sqlalchemy import create_engine from sqlalchemy.orm import Session -from parasect.core.parsing import iterate_over_dir, parse_fasta_file, write_fasta_file +from parasect.core.parsing import iterate_over_dir, parse_fasta_file +from parasect.core.writers import write_fasta_file from parasect.core.tabular import Tabular from parasect.database.populate_database import populate_db From 03aaa4c5bc4a070dd936379e82a3ab6ca5ea8e85 Mon Sep 17 00:00:00 2001 From: David Meijer Date: Fri, 5 Sep 2025 16:07:26 +0200 Subject: [PATCH 20/65] UPD: make sure no env files are being pushed --- .gitignore | 1 + 1 file changed, 1 insertion(+) diff --git a/.gitignore b/.gitignore index 3b36f98..ab2d534 100644 --- a/.gitignore +++ b/.gitignore @@ -122,6 +122,7 @@ celerybeat.pid # Environments .env +.env.* .venv env/ venv/ From a08aed4951e6ddcfa913b87af132ab36ee5edf26 Mon Sep 17 00:00:00 2001 From: David Meijer Date: Fri, 5 Sep 2025 16:07:35 +0200 Subject: [PATCH 21/65] ENH: adding captcha --- app/Dockerfile.client | 4 + app/docker-compose.yml | 2 + app/src/client/package-lock.json | 17 ++ app/src/client/package.json | 1 + app/src/client/src/pages/annotation_editor.js | 221 +++++++++++------- app/src/server/routes/annotation_editor.py | 34 ++- 6 files changed, 192 insertions(+), 87 deletions(-) diff --git a/app/Dockerfile.client b/app/Dockerfile.client index 5529c33..c0715a7 100644 --- a/app/Dockerfile.client +++ b/app/Dockerfile.client @@ -5,6 +5,10 @@ FROM node:20-alpine as build WORKDIR /app +# Provide the site key at build time (public value) +ARG REACT_APP_TURNSTILE_SITE_KEY +ENV REACT_APP_TURNSTILE_SITE_KEY=${REACT_APP_TURNSTILE_SITE_KEY} + # Install dependencies with cache-friendly order COPY ./src/client/package.json ./src/client/package-lock.json ./ RUN npm ci diff --git a/app/docker-compose.yml b/app/docker-compose.yml index 4e63ff0..96301d6 100644 --- a/app/docker-compose.yml +++ b/app/docker-compose.yml @@ -35,6 +35,8 @@ services: build: context: . dockerfile: Dockerfile.client + args: + - REACT_APP_TURNSTILE_SITE_KEY=${REACT_APP_TURNSTILE_SITE_KEY} image: paras-client ports: - "4010:80" diff --git a/app/src/client/package-lock.json b/app/src/client/package-lock.json index 9cf73ca..966a5f5 100644 --- a/app/src/client/package-lock.json +++ b/app/src/client/package-lock.json @@ -21,6 +21,7 @@ "react-router-dom": "^6.14.2", "react-scripts": "5.0.1", "react-toastify": "^9.1.3", + "react-turnstile": "^1.1.4", "smiles-drawer": "^2.1.7" } }, @@ -15371,6 +15372,16 @@ "react-dom": ">=16.6.0" } }, + "node_modules/react-turnstile": { + "version": "1.1.4", + "resolved": "https://registry.npmjs.org/react-turnstile/-/react-turnstile-1.1.4.tgz", + "integrity": "sha512-oluyRWADdsufCt5eMqacW4gfw8/csr6Tk+fmuaMx0PWMKP1SX1iCviLvD2D5w92eAzIYDHi/krUWGHhlfzxTpQ==", + "license": "MIT", + "peerDependencies": { + "react": ">= 16.13.1", + "react-dom": ">= 16.13.1" + } + }, "node_modules/read-cache": { "version": "1.0.0", "resolved": "https://registry.npmjs.org/read-cache/-/read-cache-1.0.0.tgz", @@ -29566,6 +29577,12 @@ "prop-types": "^15.6.2" } }, + "react-turnstile": { + "version": "1.1.4", + "resolved": "https://registry.npmjs.org/react-turnstile/-/react-turnstile-1.1.4.tgz", + "integrity": "sha512-oluyRWADdsufCt5eMqacW4gfw8/csr6Tk+fmuaMx0PWMKP1SX1iCviLvD2D5w92eAzIYDHi/krUWGHhlfzxTpQ==", + "requires": {} + }, "read-cache": { "version": "1.0.0", "resolved": "https://registry.npmjs.org/read-cache/-/read-cache-1.0.0.tgz", diff --git a/app/src/client/package.json b/app/src/client/package.json index ddeb0f9..8a9cf66 100644 --- a/app/src/client/package.json +++ b/app/src/client/package.json @@ -16,6 +16,7 @@ "react-router-dom": "^6.14.2", "react-scripts": "5.0.1", "react-toastify": "^9.1.3", + "react-turnstile": "^1.1.4", "smiles-drawer": "^2.1.7" }, "scripts": { diff --git a/app/src/client/src/pages/annotation_editor.js b/app/src/client/src/pages/annotation_editor.js index 193810a..90b5686 100644 --- a/app/src/client/src/pages/annotation_editor.js +++ b/app/src/client/src/pages/annotation_editor.js @@ -7,6 +7,136 @@ import { MdClose } from 'react-icons/md'; import Loading from '../components/Loading'; import ProteinTile from '../components/ProteinTile'; +import Turnstile from 'react-turnstile'; + + +const SITE_KEY = process.env.REACT_APP_TURNSTILE_SITE_KEY; + + +function SubmitAnnotationsModal({ open, onClose, proteinAnnotations }) { + const [captchaToken, setCaptchaToken] = useState(null); + const [submitting, setSubmitting] = useState(false); + const [turnstileKey, setTurnstileKey] = useState(0); // force reset when modal re-opens + + useEffect(() => { + if (open) { + // reset widget each time the modal opens + setCaptchaToken(null); + setTurnstileKey(k => k + 1); + } + }, [open]); + + {/* Submit updated protein data */} + const handleSubmit = async () => { + if (submitting) return; // prevent multiple submissions + + if (Object.keys(proteinAnnotations).length === 0) { + toast.error("No annotations to submit"); + return; + }; + + if (!captchaToken) return; + setSubmitting(true); + + try { + const res = await fetch("/api/submit_annotations", { + method: "POST", + headers: {"Content-Type": "application/json"}, + body: JSON.stringify({ + annotations: proteinAnnotations, + turnstileToken: captchaToken + }), + credentials: 'include' // include cookies + }); + + if (!res.ok) { + const err = await res.json().catch(() => ({})); + throw new Error(err?.error || "Submission failed") + } + + // success UI + onClose(); + } catch(e) { + console.error(e); + toast.error(`Error: ${e.message}`, { autoClose: false }); + } finally { + setSubmitting(false); + setCaptchaToken(null); + setTurnstileKey(k => k + 1); // reset widget after submit + } + }; + + return ( + + + + + Submit annotations + + + + + + + + {/* Turnstile widget */} + setCaptchaToken(token)} + onExpire={() => setCaptchaToken(null)} + onError={() => setCaptchaToken(null)} + // options={{ theme: 'auto', appearance: 'always' }} // optional + /> + + + + + ) +}; + + /** * Component to display the results of the prediction. * @@ -55,34 +185,6 @@ const AnnotationEditor = () => { return updated; }); }; - {/* Submit updated protein data */} - const handleSubmit = async () => { - - if (Object.keys(proteinAnnotations).length === 0) { - toast.error("No annotations to submit"); - return; - }; - - // Placeholder: validations can go here later - // For example: - // for (const [domainId, annotation] of Object.entries(domainAnnotations)) { - // ... perform checks ... - // } - - // Submit to backend to create PR - const res = await fetch("/api/submit_annotations", { - method: "POST", - headers: { "Content-Type": "application/json" }, - body: JSON.stringify({ annotations: proteinAnnotations }), - }); - - const json = await res.json(); - if (res.ok) { - toast.success(`GitHub issue created for annotations at: ${json.pr_url}`); - } else { - toast.error(`Error: ${json.error}`, { autoClose: false }); - } - }; const OpenAnnotationsSubmissionsModal = () => { setOpenAnnotationsSubmissionModal(true); @@ -252,64 +354,11 @@ const AnnotationEditor = () => { {/* Dialogue modal */} - - - - - Submit annotations - - - - - - - - - - - - - + ); diff --git a/app/src/server/routes/annotation_editor.py b/app/src/server/routes/annotation_editor.py index 637ac57..34b9683 100644 --- a/app/src/server/routes/annotation_editor.py +++ b/app/src/server/routes/annotation_editor.py @@ -1,6 +1,8 @@ import logging from typing import Any from flask import Blueprint, Response, request, jsonify +import requests +import os from parasect.database.query_database import get_substrates_from_smiles, \ @@ -11,6 +13,10 @@ from .database import get_db + +TURNSTILE_VERIFY_URL = "https://challenges.cloudflare.com/turnstile/v0/siteverify" + + blueprint_check_smiles = Blueprint("check_smiles", __name__) blueprint_check_substrate_name = Blueprint("check_substrate_name", __name__) blueprint_check_domain_name = Blueprint("check_domain_name", __name__) @@ -187,8 +193,34 @@ def cleanup_annotations(annotations: dict[str, dict[str, Any]]) -> dict[str, dic @blueprint_submit_annotations.route("/api/submit_annotations", methods=["POST"]) def submit_annotations(): + data = request.get_json() + + token = data.get("turnstileToken") + if not token: + return jsonify({"error": "missing_turnstile_token"}), 400 + + # Optional: capture client IP for verification + client_ip = request.headers.get("CF-Connecting-IP") or request.remote_addr + + try: + r = requests.post( + TURNSTILE_VERIFY_URL, + data={ + "secret": os.environ["TURNSTILE_SECRET_KEY"], + "response": token, + "remoteip": client_ip, + }, + timeout=5, + ) + ver = r.json() + except Exception as e: + return jsonify({"error": "turnstile_verification_failed", "detail": str(e)}), 502 + + if not ver.get("success"): + # ver contains fields like "error-codes", "action", "cdata" + return jsonify({"error": "captcha_failed", "detail": ver}), 400 + try: - data = request.get_json() annotations = data.get("annotations", {}) protein_to_entries = cleanup_annotations(annotations) From cf2a2069a534db3c0c8948353befe366396272f8 Mon Sep 17 00:00:00 2001 From: David Meijer Date: Fri, 5 Sep 2025 16:22:21 +0200 Subject: [PATCH 22/65] STY: add padding to titles in annotation submission form, make corners round when domain tile is collapsed --- app/src/client/src/components/DomainTile.js | 9 ++++++++- app/src/client/src/components/ProteinTile.js | 4 ++-- app/src/client/src/pages/annotation_editor.js | 4 ++-- 3 files changed, 12 insertions(+), 5 deletions(-) diff --git a/app/src/client/src/components/DomainTile.js b/app/src/client/src/components/DomainTile.js index 36bd614..d9d5703 100644 --- a/app/src/client/src/components/DomainTile.js +++ b/app/src/client/src/components/DomainTile.js @@ -370,11 +370,18 @@ const DomainTile = ({result, domainIndex, protein_name, onAnnotationChange}) => alignItems: 'center', borderTopLeftRadius: '10px', borderTopRightRadius: '10px', + // add radius to bottom corners if not expanded + borderBottomLeftRadius: expanded ? '0' : '10px', + borderBottomRightRadius: expanded ? '0' : '10px', }} > {/* Left side: domain info + optional warning stacked vertically */} - + {`Domain ${parasResult['domain_nr']}: ${domainSynonym} (${parasResult['domain_start']}-${parasResult['domain_end']})`} diff --git a/app/src/client/src/components/ProteinTile.js b/app/src/client/src/components/ProteinTile.js index 5e2c913..4eceb9f 100644 --- a/app/src/client/src/components/ProteinTile.js +++ b/app/src/client/src/components/ProteinTile.js @@ -104,7 +104,7 @@ const ProteinTile = ({proteinResult, onUpdateAnnotation}) => { sx={{ backgroundColor: 'secondary.main', color: 'black.main', - padding: '14px 8px', + padding: '21px 16px', display: 'flex', marginBottom: 1, borderTopLeftRadius: '10px', @@ -116,7 +116,7 @@ const ProteinTile = ({proteinResult, onUpdateAnnotation}) => { {/* Protein name input field */} - + { - Domains which already exist in the PARAS/PARASECT dataset are displayed in grey. New domains are displayed in yellow. + Domains which already exist in the PARAS/PARASECT dataset are displayed in grey. New domains are displayed in yellow. Please review the new domains and provide annotations where possible. You can proceed with submitting domains once they are annotated. - + {/* Wrap Button in a span to support tooltip for disabled state */} - )} - - - {/* submit and refresh buttons */} - - - - + } label='FASTA' /> + } label='GBK' /> + + + )} + + {/* text field or file upload */} + + {inputMethod === 'paste' && ( + setSelectedInput(e.target.value)} + margin='normal' + placeholder={`Paste your ${selectedInputType.toUpperCase()} content here`} + /> + )} + + {inputMethod === 'ncbi' && ( + setSelectedInput(e.target.value)} + margin='normal' + placeholder='Paste your NCBI protein accessions here' + /> + )} + + {inputMethod === 'upload' && ( + + + {uploadLabel} + + - - ); + )} + + {/* load example button */} + {inputMethod === 'paste' && ( + + )} + + + {/* submit and refresh buttons */} + + + + + + + ); }; -export default DataAnnotation; +export default DataAnnotation; \ No newline at end of file From f006f87201fe23660b7ba59c1fdd356d834d7a8e Mon Sep 17 00:00:00 2001 From: David Meijer Date: Fri, 5 Sep 2025 22:47:25 +0200 Subject: [PATCH 27/65] STY: add check mark when domain is annotated --- app/src/client/src/components/DomainTile.js | 26 +++++++++++++++++---- 1 file changed, 22 insertions(+), 4 deletions(-) diff --git a/app/src/client/src/components/DomainTile.js b/app/src/client/src/components/DomainTile.js index d9d5703..1da88fb 100644 --- a/app/src/client/src/components/DomainTile.js +++ b/app/src/client/src/components/DomainTile.js @@ -1,7 +1,8 @@ import React, {useState, useEffect, useMemo} from 'react'; import { ExpandMore, - ExpandLess + ExpandLess, + CheckCircle } from '@mui/icons-material'; import { @@ -15,6 +16,7 @@ import { Collapse, IconButton, Typography, + Tooltip } from '@mui/material'; import {FaFingerprint} from 'react-icons/fa'; @@ -46,6 +48,7 @@ const DomainTile = ({result, domainIndex, protein_name, onAnnotationChange}) => const matchedSubstrates = hasSequenceMatch ? firstSequenceMatch["substrates"] : null; const [overrideSubstrates, setOverrideSubstrates] = useState(false); const [annotationType, setAnnotationType] = useState(null); + const isAnnotated = useMemo(() => Boolean(annotationType), [annotationType]); const [proteinName, setProteinName] = useState(protein_name || ''); @@ -396,9 +399,23 @@ const DomainTile = ({result, domainIndex, protein_name, onAnnotationChange}) => {/* Right side: expand/collapse button */} - + {/* {expanded ? : } - + */} + + {isAnnotated && ( + + + + )} + + {expanded ? : } + + {/* Collapsible content */} @@ -453,7 +470,8 @@ const DomainTile = ({result, domainIndex, protein_name, onAnnotationChange}) => setOverrideSubstrates(checked); if (!checked) { setSubstrates([]); - onAnnotationChange?.(domainName, [], annotationType); + setAnnotationType(null); + onAnnotationChange?.(domainName, [], null); } }} /> From 27910c460d4a3ed7e3b81b3125e31d6fd8478076 Mon Sep 17 00:00:00 2001 From: David Meijer Date: Fri, 5 Sep 2025 22:53:44 +0200 Subject: [PATCH 28/65] ENH: open PR url in separate tab upon data submission --- app/src/client/src/pages/annotation_editor.js | 15 ++++++++++----- 1 file changed, 10 insertions(+), 5 deletions(-) diff --git a/app/src/client/src/pages/annotation_editor.js b/app/src/client/src/pages/annotation_editor.js index 6f176ce..a38e4f8 100644 --- a/app/src/client/src/pages/annotation_editor.js +++ b/app/src/client/src/pages/annotation_editor.js @@ -39,6 +39,8 @@ function SubmitAnnotationsModal({ open, onClose, proteinAnnotations }) { if (!captchaToken) return; setSubmitting(true); + + const pr_url = null; try { const res = await fetch("/api/submit_annotations", { @@ -51,16 +53,19 @@ function SubmitAnnotationsModal({ open, onClose, proteinAnnotations }) { credentials: 'include' // include cookies }); - // const data = - // (res.headers.get("content-type") || "").includes("application/json") - // ? await res.json() - // : null; + const data = await res.json(); + pr_url = data.pr_url; if (!res.ok) { const err = await res.json().catch(() => ({})); throw new Error(err?.error || "Submission failed") } + // open PR url in separate tab + if (pr_url) { + window.open(pr_url, "_blank"); + } + // success UI toast.success("Annotations submitted successfully"); onClose?.(); @@ -137,7 +142,7 @@ function SubmitAnnotationsModal({ open, onClose, proteinAnnotations }) { onClick={handleSubmit} disabled={!captchaToken || submitting} > - {submitting ? 'Submitting…' : 'Submit'} + {submitting ? 'Submitting…' : `Submit ${Object.keys(proteinAnnotations).length} annotated protein(s)`} From bcc67387a19081d2df2233491898e823c3d74bd3 Mon Sep 17 00:00:00 2001 From: David Meijer Date: Sat, 6 Sep 2025 00:12:43 +0200 Subject: [PATCH 29/65] ENH: add and valdiate ORCID and published articles --- app/src/client/src/pages/annotation_editor.js | 360 +++++++++++++++++- 1 file changed, 349 insertions(+), 11 deletions(-) diff --git a/app/src/client/src/pages/annotation_editor.js b/app/src/client/src/pages/annotation_editor.js index a38e4f8..410680e 100644 --- a/app/src/client/src/pages/annotation_editor.js +++ b/app/src/client/src/pages/annotation_editor.js @@ -1,8 +1,10 @@ -import React, { useEffect, useState } from 'react'; +import React, { useEffect, useState, useMemo } from 'react'; import { useParams } from 'react-router-dom'; import { toast } from 'react-toastify'; -import { Box, IconButton, Divider, Typography, Button, Modal, Tooltip } from '@mui/material'; +import { Box, IconButton, Divider, Typography, Button, Modal, Tooltip, TextField, Stack, Chip, CircularProgress } from '@mui/material'; +import { CheckCircle, ErrorOutline } from "@mui/icons-material"; import { MdClose } from 'react-icons/md'; + import { useNavigate } from "react-router-dom"; import Loading from '../components/Loading'; @@ -20,15 +22,251 @@ function SubmitAnnotationsModal({ open, onClose, proteinAnnotations }) { const [submitting, setSubmitting] = useState(false); const [turnstileKey, setTurnstileKey] = useState(0); // force reset when modal re-opens + // ORCID state + const [orcidInput, setOrcidInput] = useState(""); + const [orcidNormalized, setOrcidNormalized] = useState(""); + const [orcidError, setOrcidError] = useState(""); + + // Reference (DOI / PMID) + const [refInput, setRefInput] = useState(""); + const [references, setReferences] = useState([]); // [{key,type:'doi'|'pmid', id, status:'pending'|'valid'|'invalid'|'error', title?, url?}] + const MAX_REFS = 20; + useEffect(() => { if (open) { // reset widget each time the modal opens setCaptchaToken(null); setTurnstileKey(k => k + 1); + + setOrcidInput(""); + setOrcidNormalized(""); + setOrcidError(""); + + setRefInput(""); + setReferences([]); } }, [open]); - {/* Submit updated protein data */} + // ----- ORCID helpers ----- + const normalizeOrcid = (value) => { + if (!value) return ''; + // Strip URL prefix if present + const cleaned = value + .trim() + .replace(/^https?:\/\/(www\.)?orcid\.org\//i, '') + .replace(/[^0-9xX]/g, ''); // keep digits and X + // Allow last char X, others must be digits; length should be 16 + return cleaned.toUpperCase(); + }; + + const formatOrcidPretty = (digits16) => { + // returns 0000-0000-0000-0000 + return `${digits16.slice(0,4)}-${digits16.slice(4,8)}-${digits16.slice(8,12)}-${digits16.slice(12,16)}`; + }; + + // ISO 7064 mod 11-2 checksum for ORCID (last char may be 'X' which means 10) + const isValidOrcid = (digits16) => { + if (!/^\d{15}[\dX]$/.test(digits16)) return false; + let total = 0; + for (let i = 0; i < 15; i++) { + total = (total + parseInt(digits16[i], 10)) * 2; + } + const remainder = total % 11; + const result = (12 - remainder) % 11; + const checkChar = result === 10 ? 'X' : String(result); + return checkChar === digits16[15]; + }; + + const handleOrcidChange = (e) => { + const raw = e.target.value; + setOrcidInput(raw); + + const normalized = normalizeOrcid(raw); + if (normalized.length === 16 && isValidOrcid(normalized)) { + setOrcidNormalized(formatOrcidPretty(normalized)); + setOrcidError(''); + } else { + setOrcidNormalized(''); + // only show error once user has typed enough chars that could plausibly be an ORCID + if (normalized.length >= 12) { + setOrcidError('Invalid ORCID. Expected format 0000-0000-0000-000X with a valid checksum.'); + } else { + setOrcidError(''); + } + } + }; + + // ----- Reference helpers ----- + const parseRefToken = (token) => { + const t = token.trim(); + if (!t) return null; + + // Strip URL wrappers + const stripped = t + .replace(/^https?:\/\/(dx\.)?doi\.org\//i, "") + .replace(/^https?:\/\/pubmed\.ncbi\.nlm\.nih\.gov\//i, "") + .replace(/^pmid:\s*/i, ""); + + // DOI regex (from Crossref guide) + const doiRegex = /^10\.\d{4,9}\/[-._;()/:A-Z0-9]+$/i; + if (doiRegex.test(stripped)) { + return { type: "doi", id: stripped }; + } + + // PMID (digits only, typical up to 8-9 digits) + const pmidRegex = /^\d{1,9}$/; + if (pmidRegex.test(stripped)) { + return { type: "pmid", id: stripped }; + } + + return null; + }; + + const addReferencesFromInput = async () => { + if (!refInput.trim()) return; + + const tokens = refInput + .split(/[\s,;\n]+/) // spaces, commas, semicolons, newlines + .map((x) => x.trim()) + .filter(Boolean); + + let current = [...references]; + const seen = new Set(current.map((r) => `${r.type}:${r.id}`)); + + for (const tok of tokens) { + if (current.length >= MAX_REFS) break; + const parsed = parseRefToken(tok); + if (!parsed) continue; + const key = `${parsed.type}:${parsed.id}`.toLowerCase(); + if (seen.has(key)) continue; + + seen.add(key); + current.push({ + key, + ...parsed, + status: "pending", + title: undefined, + url: undefined, + }); + } + + if (current.length > references.length) { + setReferences(current); + setRefInput(""); + // validate the new ones + const newOnes = current.filter((r) => r.status === "pending"); + for (const ref of newOnes) { + validateReference(ref); + } + } else { + // nothing added + setRefInput(""); + } + }; + + const removeReference = (key) => { + setReferences((prev) => prev.filter((r) => r.key !== key)); + }; + + const markRef = (key, patch) => { + setReferences((prev) => prev.map((r) => (r.key === key ? { ...r, ...patch } : r))); + }; + + // Crossref for DOI + const validateViaCrossref = async (doi) => { + const url = `https://api.crossref.org/works/${encodeURIComponent(doi)}`; + const res = await fetch(url, { headers: { Accept: "application/json" } }); + if (!res.ok) throw new Error(`Crossref ${res.status}`); + const json = await res.json(); + const msg = json?.message; + if (!msg) return { valid: false }; + + const type = msg.type; // 'journal-article', 'posted-content' (preprint), etc. + const issued = msg.issued; // date parts if available + const isPreprint = type === "posted-content"; + const isPublished = !!issued && !isPreprint; + + const title = (Array.isArray(msg.title) && msg.title[0]) || doi; + const urlOut = msg.URL || `https://doi.org/${doi}`; + + return { valid: Boolean(isPublished), title, url: urlOut }; + }; + + // PubMed E-utilities for PMID + const validateViaPubMed = async (pmid) => { + const url = `https://eutils.ncbi.nlm.nih.gov/entrez/eutils/esummary.fcgi?db=pubmed&id=${encodeURIComponent( + pmid + )}&retmode=json`; + const res = await fetch(url); + if (!res.ok) throw new Error(`NCBI ${res.status}`); + const json = await res.json(); + const rec = json?.result?.[pmid]; + if (!rec) return { valid: false }; + + const title = rec.title || `PMID:${pmid}`; + // consider "published" if has a pubdate and is not preprint. PubMed labels preprints differently + const hasDate = Boolean(rec.pubdate || rec.epubdate || rec.sortpubdate); + const isPreprint = + Array.isArray(rec.pubtype) && rec.pubtype.some((pt) => /preprint/i.test(pt)); // conservative + const valid = hasDate && !isPreprint; + + const urlOut = `https://pubmed.ncbi.nlm.nih.gov/${pmid}/`; + return { valid, title, url: urlOut }; + }; + + const validateReference = async (ref) => { + try { + if (ref.type === "doi") { + const { valid, title, url } = await validateViaCrossref(ref.id); + markRef(ref.key, { status: valid ? "valid" : "invalid", title, url }); + } else if (ref.type === "pmid") { + const { valid, title, url } = await validateViaPubMed(ref.id); + markRef(ref.key, { status: valid ? "valid" : "invalid", title, url }); + } else { + markRef(ref.key, { status: "invalid" }); + } + } catch (e) { + // Fallback to backend if CORS/network fails + // TODO: implement server endpint to validate reference + try { + const res = await fetch("/api/validate_reference", { + method: "POST", + headers: { "Content-Type": "application/json" }, + body: JSON.stringify({ type: ref.type, id: ref.id }), + }); + if (res.ok) { + const j = await res.json(); + const { valid, title, url } = j || {}; + markRef(ref.key, { status: valid ? "valid" : "invalid", title, url }); + } else { + markRef(ref.key, { status: "error" }); + } + } catch { + markRef(ref.key, { status: "error" }); + } + } + }; + + const refsPending = references.some((r) => r.status === "pending"); + const refsInvalid = references.some((r) => r.status === "invalid" || r.status === "error"); + const refsValidPayload = useMemo( + () => + references + .filter((r) => r.status === "valid") + .map(({ type, id, title, url }) => ({ type, id, title, url })), + [references] + ); + + const canSubmit = + !!captchaToken && + !submitting && + Object.keys(proteinAnnotations).length > 0 && + !!orcidNormalized && + !orcidError && + !refsPending && + !refsInvalid; + + // Submit updated protein data const handleSubmit = async () => { if (submitting) return; // prevent multiple submissions @@ -38,6 +276,19 @@ function SubmitAnnotationsModal({ open, onClose, proteinAnnotations }) { }; if (!captchaToken) return; + + // Require valid ORCID + if (!orcidNormalized || orcidError) { + setOrcidError('Please provide a valid ORCID.'); + return; + } + + // Require valid references that are not pending + if (refsPending || refsInvalid) { + toast.error("Please resolve or remove invalid/pending references."); + return; + } + setSubmitting(true); const pr_url = null; @@ -48,19 +299,21 @@ function SubmitAnnotationsModal({ open, onClose, proteinAnnotations }) { headers: {"Content-Type": "application/json"}, body: JSON.stringify({ annotations: proteinAnnotations, - turnstileToken: captchaToken + turnstileToken: captchaToken, + orcid: orcidNormalized, + references: refsValidPayload }), credentials: 'include' // include cookies }); const data = await res.json(); - pr_url = data.pr_url; if (!res.ok) { - const err = await res.json().catch(() => ({})); - throw new Error(err?.error || "Submission failed") + throw new Error(data?.error || "Submission failed") } + pr_url = data?.pr_url || null; + // open PR url in separate tab if (pr_url) { window.open(pr_url, "_blank"); @@ -122,11 +375,94 @@ function SubmitAnnotationsModal({ open, onClose, proteinAnnotations }) { sx={{ display: 'flex', flexDirection: 'column', - alignItems: 'left', + alignItems: 'flex-start', gap: 3, p: 4, }} > + {/* ORCID field */} + + + {/* References */} + + + Related publications (DOI or PubMed ID) - optional + + + + setRefInput(e.target.value)} + helperText={`${references.length}/${MAX_REFS} added`} + /> + + + + {!!references.length && ( + + {references.map((r) => { + const color = + r.status === "valid" ? "success" : r.status === "pending" ? "default" : "error"; + const icon = + r.status === "valid" ? ( + + ) : r.status === "pending" ? ( + + ) : ( + + ); + const label = + r.type === "doi" ? `DOI:${r.id}` : r.type === "pmid" ? `PMID:${r.id}` : r.id; + + return ( + + removeReference(r.key)} + variant={r.status === "valid" ? "filled" : "outlined"} + /> + + ); + })} + + )} + + {refsInvalid && ( + + Some references are invalid or not recognized as published articles. Remove or correct them to submit. + + )} + {refsPending && ( + + Validating references… + + )} + + {/* Turnstile widget */} setCaptchaToken(token)} onExpire={() => setCaptchaToken(null)} onError={() => setCaptchaToken(null)} - // options={{ theme: 'auto', appearance: 'always' }} // optional + options={{ theme: 'auto', appearance: 'always' }} /> From e49c81cabe5e5c12c7c4b28e0480338918f31bcb Mon Sep 17 00:00:00 2001 From: David Meijer Date: Sat, 6 Sep 2025 00:20:08 +0200 Subject: [PATCH 30/65] ENH: forward orcid and references into github submission --- app/src/server/routes/annotation_editor.py | 13 +++++++--- src/parasect/core/github.py | 28 ++++++++++++++++++---- 2 files changed, 33 insertions(+), 8 deletions(-) diff --git a/app/src/server/routes/annotation_editor.py b/app/src/server/routes/annotation_editor.py index 34b9683..0d268fd 100644 --- a/app/src/server/routes/annotation_editor.py +++ b/app/src/server/routes/annotation_editor.py @@ -222,10 +222,13 @@ def submit_annotations(): try: annotations = data.get("annotations", {}) + orcid = data.get("orcid", "") + references = data.get("references", []) + protein_to_entries = cleanup_annotations(annotations) # Create a GitHub PR with annotations - pr_url = create_github_issue(protein_to_entries) + pr_url = create_github_issue(protein_to_entries, orcid, references) return jsonify({"pr_url": pr_url}), 200 @@ -234,7 +237,11 @@ def submit_annotations(): return jsonify({"error": str(e)}), 500 -def create_github_issue(annotations: dict[str, dict[str, Any]]) -> str: +def create_github_issue( + annotations: dict[str, dict[str, Any]], + orcid: str, + references: list[dict[str, str]] +) -> str: """ Create one GitHub issue per protein @@ -245,7 +252,7 @@ def create_github_issue(annotations: dict[str, dict[str, Any]]) -> str: """ session_generator = get_db() session = next(session_generator) - submit_github_issues(session, annotations) + submit_github_issues(session, annotations, orcid, references) return "https://github.com/BTheDragonMaster/parasect/issues" diff --git a/src/parasect/core/github.py b/src/parasect/core/github.py index 1b6ba90..53be274 100644 --- a/src/parasect/core/github.py +++ b/src/parasect/core/github.py @@ -76,12 +76,21 @@ class DomainEntry: entry_type: EntryType -def submit_github_issue_protein(protein_entry, domains, new_substrates, annotation_type: EntryType): +def submit_github_issue_protein( + protein_entry, + domains, + new_substrates, + annotation_type: EntryType, + orcid: str = "", + references: list[dict[str, str]] = [] +): url = f"https://api.github.com/repos/{REPO}/issues" headers = {"Authorization": f"token {GITHUB_TOKEN}"} title = f"[{EntryType.to_header(annotation_type)}] {protein_entry.name}" body_dict = { + "orcid": orcid, + "references": references, "protein_name": protein_entry.name, "protein_sequence": protein_entry.sequence, "new_substrates": [{"name": substrate.name, "smiles": substrate.smiles} for substrate in new_substrates], @@ -104,13 +113,22 @@ def submit_github_issue_protein(protein_entry, domains, new_substrates, annotati return response.json() -def submit_github_issues(session: Session, protein_to_entry: dict[str, dict[str, Any]]) -> None: +def submit_github_issues( + session: Session, + protein_to_entry: dict[str, dict[str, Any]], + orcid: str, + references: list[dict[str, str]] +) -> None: """Submit GitHub new annotations, one per protein per annotation type, to BTheDragonMaster/parasect as issues :param session: Database session :type session: Session :param protein_to_entry: dictionary of protein names as keys and protein and domain annotations as (nested) values :type protein_to_entry: dict[str, dict[str, Any]] + :param orcid: ORCID ID of the user submitting the annotations + :type orcid: str + :param references: list of references to include in the issue + :type references: list[dict[str, str]] """ for protein_name, protein_info in protein_to_entry.items(): protein_entry = ProteinEntry(protein_name, protein_info["sequence"]) @@ -169,11 +187,11 @@ def submit_github_issues(session: Session, protein_to_entry: dict[str, dict[str, raise ValueError(f"Unrecognised entry type: {domain_entry.entry_type.name}") if corrections: - submit_github_issue_protein(protein_entry, corrections, substrates_corrections, EntryType.CORRECTION) + submit_github_issue_protein(protein_entry, corrections, substrates_corrections, EntryType.CORRECTION, orcid, references) if new_entries: - submit_github_issue_protein(protein_entry, new_entries, substrates_new_entries, EntryType.NEW) + submit_github_issue_protein(protein_entry, new_entries, substrates_new_entries, EntryType.NEW, orcid, references) if duplicate_entries: - submit_github_issue_protein(protein_entry, duplicate_entries, substrates_duplicates, EntryType.DUPLICATE) + submit_github_issue_protein(protein_entry, duplicate_entries, substrates_duplicates, EntryType.DUPLICATE, orcid, references) def fetch_github_issues(token, filter_strings=None, state="all"): From ceed11ae7e7d94fea0acb858d02e42ce3fa2a701 Mon Sep 17 00:00:00 2001 From: David Meijer Date: Sat, 6 Sep 2025 00:23:52 +0200 Subject: [PATCH 31/65] FIX: make sure prUrl is mutable --- app/src/client/src/pages/annotation_editor.js | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/app/src/client/src/pages/annotation_editor.js b/app/src/client/src/pages/annotation_editor.js index 410680e..a829fbb 100644 --- a/app/src/client/src/pages/annotation_editor.js +++ b/app/src/client/src/pages/annotation_editor.js @@ -291,7 +291,7 @@ function SubmitAnnotationsModal({ open, onClose, proteinAnnotations }) { setSubmitting(true); - const pr_url = null; + let prUrl = null; try { const res = await fetch("/api/submit_annotations", { @@ -312,11 +312,11 @@ function SubmitAnnotationsModal({ open, onClose, proteinAnnotations }) { throw new Error(data?.error || "Submission failed") } - pr_url = data?.pr_url || null; + prUrl = data?.prUrl || null; // open PR url in separate tab - if (pr_url) { - window.open(pr_url, "_blank"); + if (prUrl) { + window.open(prUrl, "_blank"); } // success UI @@ -393,7 +393,7 @@ function SubmitAnnotationsModal({ open, onClose, proteinAnnotations }) { {/* References */} - + Related publications (DOI or PubMed ID) - optional From cffe8ed79c766874d81b75b0a6ba04dbed237d82 Mon Sep 17 00:00:00 2001 From: David Meijer Date: Sat, 6 Sep 2025 00:31:15 +0200 Subject: [PATCH 32/65] FIX: read out correct value for pr_url --- app/src/client/src/pages/annotation_editor.js | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/app/src/client/src/pages/annotation_editor.js b/app/src/client/src/pages/annotation_editor.js index a829fbb..487c753 100644 --- a/app/src/client/src/pages/annotation_editor.js +++ b/app/src/client/src/pages/annotation_editor.js @@ -312,7 +312,8 @@ function SubmitAnnotationsModal({ open, onClose, proteinAnnotations }) { throw new Error(data?.error || "Submission failed") } - prUrl = data?.prUrl || null; + prUrl = data?.pr_url || null; + console.log(prUrl); // open PR url in separate tab if (prUrl) { From 5ab62d5204b7aa71603ef54168f0a387e6b1c133 Mon Sep 17 00:00:00 2001 From: David Meijer Date: Sat, 6 Sep 2025 00:36:50 +0200 Subject: [PATCH 33/65] UPD: return json data in markdown format --- src/parasect/core/github.py | 14 +++++++------- 1 file changed, 7 insertions(+), 7 deletions(-) diff --git a/src/parasect/core/github.py b/src/parasect/core/github.py index 53be274..aa5cb92 100644 --- a/src/parasect/core/github.py +++ b/src/parasect/core/github.py @@ -101,16 +101,16 @@ def submit_github_issue_protein( "substrates": [s.name for s in domain.substrates]} for domain in domains] } - body = json.dumps(body_dict, indent=2) + body_md = f"```json\n{json.dumps(body_dict, indent=2)}\n```" + payload = {"title": title, "body": body_md} - issue = {"title": title, "body": body} - response = requests.post(url, json=issue, headers=headers) + resp = requests.post(url, json=payload, headers=headers) - # evaluate response code and throw error if not good - if response.status_code != 201: - raise ValueError(f"Failed to create GitHub issue: {response.text}") + if resp.status_code != 201: + # include response body to help debugging + raise ValueError(f"Failed to create GitHub issue ({resp.status_code}): {resp.text}") - return response.json() + return resp.json() def submit_github_issues( From f735586a149772b151d5e2d54ca2c48098032c9d Mon Sep 17 00:00:00 2001 From: David Meijer Date: Sat, 6 Sep 2025 22:49:24 +0200 Subject: [PATCH 34/65] ADD: button to data annotation page on home page --- app/src/client/src/pages/home.js | 11 +++++++++++ 1 file changed, 11 insertions(+) diff --git a/app/src/client/src/pages/home.js b/app/src/client/src/pages/home.js index f34ad3e..0cbd82b 100644 --- a/app/src/client/src/pages/home.js +++ b/app/src/client/src/pages/home.js @@ -72,6 +72,17 @@ const Home = () => { Retrieve results + From 13176d492fd6e895ccdf0e31eb6f5b22cca759ad Mon Sep 17 00:00:00 2001 From: David Meijer Date: Sat, 6 Sep 2025 22:49:56 +0200 Subject: [PATCH 35/65] STY: update capitalization to match other items in menu --- app/src/client/src/index.js | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/app/src/client/src/index.js b/app/src/client/src/index.js index ac5fb82..c4baf44 100644 --- a/app/src/client/src/index.js +++ b/app/src/client/src/index.js @@ -137,7 +137,7 @@ const CustomToolbar = () => { handleMenuItemClick('/data_annotation')}> - Data Annotation + Data annotation handleExternalLinkClick('https://github.com/BTheDragonMaster/parasect/issues')}> From 9fbf7c87995e4b77d141e80686e635859a651e8d Mon Sep 17 00:00:00 2001 From: David Meijer Date: Sat, 6 Sep 2025 22:57:05 +0200 Subject: [PATCH 36/65] UPD: make ORCID optional and at least one reference mandatory --- app/src/client/src/pages/annotation_editor.js | 32 +++++++++++-------- 1 file changed, 19 insertions(+), 13 deletions(-) diff --git a/app/src/client/src/pages/annotation_editor.js b/app/src/client/src/pages/annotation_editor.js index 487c753..238b827 100644 --- a/app/src/client/src/pages/annotation_editor.js +++ b/app/src/client/src/pages/annotation_editor.js @@ -257,14 +257,15 @@ function SubmitAnnotationsModal({ open, onClose, proteinAnnotations }) { [references] ); + // ORCID is optional, need at least one valid reference. However if an ORCID is provided, it must be valid. const canSubmit = !!captchaToken && !submitting && Object.keys(proteinAnnotations).length > 0 && - !!orcidNormalized && - !orcidError && + (!orcidInput.trim() || (!!orcidNormalized && !orcidError)) && !refsPending && - !refsInvalid; + !refsInvalid && + refsValidPayload.length > 0; // Submit updated protein data const handleSubmit = async () => { @@ -382,20 +383,25 @@ function SubmitAnnotationsModal({ open, onClose, proteinAnnotations }) { }} > {/* ORCID field */} - + + + Contributor ORCID - optional + + + {/* References */} - Related publications (DOI or PubMed ID) - optional + Related publications (DOI or PubMed ID) - at least one required From b4e540cf17e184bb033b07ee18d59f5808541821 Mon Sep 17 00:00:00 2001 From: "Terlouw, Barbara" Date: Mon, 8 Sep 2025 13:09:25 +0200 Subject: [PATCH 37/65] Fix substrate --- src/parasect/data/database_files/parasect_dataset.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/parasect/data/database_files/parasect_dataset.txt b/src/parasect/data/database_files/parasect_dataset.txt index 6fe1948..8ea81ec 100644 --- a/src/parasect/data/database_files/parasect_dataset.txt +++ b/src/parasect/data/database_files/parasect_dataset.txt @@ -3577,7 +3577,7 @@ ctg1_orf1265.A3 AEQAARTPEAVALVAGGRVWSFAELDARVNRFARLLLARGAGPEKVVALGLPRSLEMVAALFAV ctg1_orf20.A1 FERQVGLASDSVALVYEDRKLTYAELNAAANRLARLLAARGVGAEDIVAVALPRSPELVVCLLAVMKAGAAYLPLDADHPPDRIAYMLDDAGARTVVTTRELSADLPTTPRIERVFLDEPSVAAECAALDAANPSMPVALDQAAYVIYTSGSTGRPKGVVLSHDGVGSLIATATERIGITTDSRVVQFASVGFDVTVWELIMALCVGGRIIVVPTERRVASPALTDYIARHRATHMALPPSLVSALPRDCELPDGAVLLVGTEAVPSELIARWAGRLQVVVAYGLTEATVNSTLWIAEQDRPGPAPIGRPDPNTRAYVLDSALRPVPVGSEGELYVSGRGLARGYLGRPGLTSERFVADPFAERPGTRMYRTGDRVRWSVDGNLEFLGRTDGQIKIRGHRIEPGEIESAFMACPGIAQAAVLVREDHRQVKRLVAYLVAESGTDAEAAVAEARATIAGVLPDYMVPSAVVRLDGPLPLTPNGK N5-acetyl-N5-hydroxyornithine ctg1_orf20.A2 RQARRTPDATALIHEDGRTTYADLDARAEALAGRLVAQGVTPGSVVAVAVPRSAEALAALLGVLKAGAAYLPVDVDHPADRIRYLLEDAGARTVVVTAASQTRLPLLDGVTHVLLGADKPVPAPVAMSVHPDDAAYVIYTSGSTGRPKGVVVSHRAATSQLAWTAERFGFGPGERVLHQYSTSFDPSLLEIFTPLLTGGTVVIARPDGHRDPAYLVDLVRRERVTSIDLVPSLYGALLAEEGPDEWWATLRRAFSGGESLPAPLARRWRERTGVPLFNVYGPTEATVQVTSWEAGSCTEDAGTIPIGRPVSNTRLYVLDAYLRPMAAGEPGELYIAGAQLAHGYLGRPGLTAERFVADPFGGPGERMYRTGDMVQFSGDGVLTYLGRTDHQVKIRGNRVELGEIEARLRDEPAVGDAVVVAREDERRVKQLVAYLVPAAGARELDTEAVRAALTGSLPAAMVPGHFVRLDALPLTPGGK arginine ctg1_orf20.A3 TAQVARTPDAVALVFGERALTYAELDAHINRIARLLLARGAGPERTVALALPRSIEMVAALFAVLRTGAAYLPLDLDHPADRLRLMVADTGPLCLLSTTAVAPALRGEAGPLAPEVLLDDEAVVAELVGLPGGEVSDAERPAFAQDRVDRLEHPAYVIYTSGSTGKPKGVVTPYRGLTNMQLNHQKEIFDPAIASAGGRRLRIAHTVSFAFDMSWEELLWLVEGHEVHVCDEELRRDAEALVAYCDSHRIDVVNVTPTYARLLIEEGLLDHDEEAGKHRPALVLLGGEAVSDTVWTKLRRTDGTYGYNLYGPTEYTINTLGGSTTDSATPTVGLPIRNTRAYVLDAMLRPVPPGCPGELYIAGTGLARGYHDRPGLSAERFVADPFGAPGMRMYRTGDLVRQRPDGLLDFLGRTDDQVKIRGYRIELGEIAAALSAHPEVAHAAVIVSEATGSKRLVGYFVPEAGAEAGEELLQRLREQVKAGLPDYMVPAALVPVATLPLTVNGK N5-hydroxyornithine -ctg1_orf20.A4 FARRLAERPDAVAVVDHARSLTYERLDARANRTARLLAAHGVGAESVVGVAVPRSADMIATVLAVLKLGAAFLPLDLAQPADRLAHMIEDSGAALVVGTEPVAGKIPPVADVPLVLLDAPQTATELEALSEAAIEGVRVGLDQAAYVIYTSGSTGRPKGVVVPHEGIASLVATAVDRMGLEPDSRVLQFASIGFDVFVFELAMALCHGGRLVLITDEARVAGPALTDFLTDQRITHMILPPSLVSALPPGCELPEGSTVLVGTETVPPDLFERFGATANLICAYGLTEATVNSTLWAAREYGGRPGGRVPIGRPDPNTRCYVLDDQLRPVPPGVVGELYVAGRGLALGYLGRAGLTSERFVADPFGAAGRRMYRTGDRARWRADGNLDFLGRVDTQVKVRGFRIELGEIEAALASHPSVAQAAVLPDRDGDIVRLIGYAVPESGEPDPQELRAHVAGLVPEYMVPTLVVALDGPLPLTPNGK N5-acetyl-hydroxyornithine +ctg1_orf20.A4 FARRLAERPDAVAVVDHARSLTYERLDARANRTARLLAAHGVGAESVVGVAVPRSADMIATVLAVLKLGAAFLPLDLAQPADRLAHMIEDSGAALVVGTEPVAGKIPPVADVPLVLLDAPQTATELEALSEAAIEGVRVGLDQAAYVIYTSGSTGRPKGVVVPHEGIASLVATAVDRMGLEPDSRVLQFASIGFDVFVFELAMALCHGGRLVLITDEARVAGPALTDFLTDQRITHMILPPSLVSALPPGCELPEGSTVLVGTETVPPDLFERFGATANLICAYGLTEATVNSTLWAAREYGGRPGGRVPIGRPDPNTRCYVLDDQLRPVPPGVVGELYVAGRGLALGYLGRAGLTSERFVADPFGAAGRRMYRTGDRARWRADGNLDFLGRVDTQVKVRGFRIELGEIEAALASHPSVAQAAVLPDRDGDIVRLIGYAVPESGEPDPQELRAHVAGLVPEYMVPTLVVALDGPLPLTPNGK N5-acetyl-N5-hydroxyornithine esyn1.A1 SQSPNKAAVAAWDGEWTYAELDDVSSRLAQHINSTDLGKDHAIVPIYFEKSKWVVASMLAVLKAGHAFTLIDPSDPPARTAQVAQQTSATVALTSKLHRETVQSTVGRCIVVDDDFVQSLHQSSELSASVKAHDLAYVIFTSGSTGDPKGIMIEHRAFSSCAIKFGPALGITSNTRALQFGSHAFGACILEIMTTLIHGGCVCIPSDDDRMNNVPEFINRTDVNWVMATPSYMGTFQPEVVPGLKTLVLVGEQMSASVNEVWAPRVQLLNGYGQSESSSICCVAKISPGSSEPNNIGHAVGAHSWIVDPEDPNRLAPIGAIGELVIESAGIARDYIVAPPQDKSPFIKTAPTWYPSKQLPDGFKIYRTGDLACYASDGSIVCLGRMDSQVKIR 2S-hydroxyisovaleric acid esyn1.A2 FREQAAANPEAIAVTDSSSRLTYAELDHQSELLSRWLRRRNLAPETLVSVLAPRSCETVVAFVGILKANLAYLPLDVRSPVARMRDILSSVSGNTIVIMGTGVEDPGFGLPQLELVHITDTFDETIQDVPNSAQPSATSLAYVVFTSGSTGKPKGVMIEHRAIVRLVKSENFRNFPSPARMSHVFNAAFDGAVWEILWMLLNGGTVVCVDYLATLDGKELAAVFAKERVNAAFLAPAMLKLYLTDAREALKNLDFLVVGGERFDAKEAKEAMTLVRGHIANIYGPTEAGIITTSYTIPADEAYTNGVPIGRSIYNSGAYIMDPNQQLVGLGVMGELVVTGDGVGRGYTNSELNKNRFVDITIEGKTFRAYRTGDRMRARVGDGLLEFFGRMDNQFKIR valine g8718.t1.A1 QKQVEARPEDPAVASWDRNLTYGELHWFASRLALRLKELGAGPDMFIPICFPKSTWAIVSMVAVNMVGAAFVPLDPSAPDERLQSILQDIQATLALAAPDHTARMSKLDIEVFTVDESIVNGLPAASADDLLSAVQPQDPSFVIFTSGSTGRPKGMVIQHSAIASTAAAYGGSLQVGPGTRVFQFSAYTFDIGVMDVMVTLMRGACVCVPSDLARVNDLAGAISSTQANWVFLTPTVASLLSPEEVPSLKTVIFGGEALPKKLVDQWKGVVQLHGVYGPAEASCCAWNPRVGESPKSTNIGTPIGSAFWVVDPASHRKLLPIGCVGELLIQGPMLSRGYLQADPKSAANWLENIDWLPDNGFGHRRGYFTGDLVRRNADGTFDYFGRKDTQVKL proline From 3b8b6b9343150e1c35743f7d444cd8cb23d6574c Mon Sep 17 00:00:00 2001 From: "Terlouw, Barbara" Date: Mon, 8 Sep 2025 13:10:12 +0200 Subject: [PATCH 38/65] Avoid duplicate substrates --- benchmarking/data_processing/nrpstransformer.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/benchmarking/data_processing/nrpstransformer.py b/benchmarking/data_processing/nrpstransformer.py index e75a5e5..6671e46 100644 --- a/benchmarking/data_processing/nrpstransformer.py +++ b/benchmarking/data_processing/nrpstransformer.py @@ -67,7 +67,8 @@ def process_nrpstransformer_data(nrpstransformer_raw_file: str, substrate_mappin for specificity in specificities: spec = abbreviation_to_spec[specificity.lower()] specs = spec.split('|') - specificity_string.extend(list(set(specs))) + specificity_string.extend(specs) + specificity_string = list(set(specificity_string)) id_to_spec[domain_name] = '|'.join(specificity_string) write_tabular([id_to_seq, id_to_spec], ["domain_id", "sequence", "specificity"], out_file) From e714d56258d63d0b398daef50b4707819d671086 Mon Sep 17 00:00:00 2001 From: "Terlouw, Barbara" Date: Mon, 8 Sep 2025 15:15:01 +0200 Subject: [PATCH 39/65] Update database with substrate corrections --- app/src/server/parasect.db | Bin 8900608 -> 8900608 bytes .../database/process_substrate_corrections.py | 0 2 files changed, 0 insertions(+), 0 deletions(-) create mode 100644 src/parasect/database/process_substrate_corrections.py diff --git a/app/src/server/parasect.db b/app/src/server/parasect.db index e3a5c1c5f15a8b92a0b57728b6c9bf544bd05f10..e1d15c95d0a7ab18d64140f7f84a8c1716d8113c 100644 GIT binary patch delta 4377 zcmb8y33wD$o&fNAuU_?CUAalpouqRh2|4H^eIyW)5Wovb5X2x?Iw24sbcY;5lqFrS z3gU;#CWG?U(P?4U*%{~H7-Jsn>Hv!DEG{l_cXq+i8DQ{Z)?*Eejx+1%?7tHj!SS2# zvy)$cRj=QB_3Hnws@T3~Nem1*ka^hIfXs(me!802%jH*I$Y^Pn(R^0tr-hQibXxw| z9=2(kNxmi!K`<3DkB4T6ou&`>{Cd+SA{>$fd_bj4^#p_2!J36fhtf9W`bFu2FwPvpbpf7IiLZ|1@pjsa67mI+zIXicY_7s z9)cH>%j)F z5p;r0AklA8&;>SwZqNgIK_7S!Yyn$AKX?c{47P#40o%ayVw`$O#b`>|~HEu?zbug(nE zndgI88r%MHER*$q5X)e;_hK@8)~c4bc}f~f7M3&=*EE(i>P0jpwGB>P`3>%8x!3Ra 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z#XAgI>T-5iQ@^RY5n>TNm49H+@|&C;`EYJy$cm3Tpm*d+>A1G3zOK5Za_EfOkt_M| zjYAQpbeBfZDcf-_chVI^X;WHwO(z}8yF2L#KDUcbj3YjbzaLQfns&$;XDfo7$m1iL zs2Z<&T;p(t&26R151Sb1qO+sXN-K)X5%+g9Su{ODyCnBBsEycX*)!}!eqVk~>Jgs( zbR|MZM8g64M-453c1wq^-+qL)_^nVpFXVpeL1-3F9-u+7d4Rqq#p*k3KYy_cV(DA- z>15*g+;$Qc67ObRziW{G1FNs{!mIQ)vGpq5 zZYSymdxU$wq6^|;Njm;n%;Y@L@)g~JVR_wkDx4^^>-0JFzn5tXwBL#I-_WcK>!B}j z+0Xiro1gZxYvTEIwoGyBRvd3cUd|Q%aqMyeIw<5KmW6muF`FW)i&>rv`MZi!_&voe zk)JDNldbk%=W>7zqLchufE^SMFJhzYv3mD9h{4d39J&VvH_9mnma`m%=+D}&a5>1P zBEOgsWOpM}#D5iH^TaY3teByXslvc5UX#J;Wr^?gBO=0#XvU)x(dYzVE9^~3fB`vQl%HXTWUGf$T<&Mv(PzA~pM51d23SqB%gG%# z=9cqv&tDiyAZm&2oR9|@%;|LQxystb{;SNu!-IVzI*tmFdyVz`td?KkvfC{39@ZY# z+O&;Ym9|uysby=anx=lCz9-7v=13&A#F*92Sbg7^pJlnWfPax<_DU)HQux)k;7dh( z`+R(ZM3cqGBg|xsUJ|n3T!DB+x;dI)ga$=>x_K`~*$~+*zHYpkBxYrrFFQ#$I&I^D zLDS3Aa?IJ-;pA00=3aD#f0JWQfQxVDsnbn2Z_G8{!CFu(%rg&QZseJ9(hm4&TLqCg z+5DUg&w`)kVDvfxx4xHPhgU69M)D{(4e_;Z>K8GC%EM74lg!3ERA;7%*@^UIlr+V8 ljz Date: Mon, 8 Sep 2025 15:15:29 +0200 Subject: [PATCH 40/65] Add code to pull domain corrections from github --- src/parasect/core/github.py | 145 +++++++++++++++++++++++------------- 1 file changed, 94 insertions(+), 51 deletions(-) diff --git a/src/parasect/core/github.py b/src/parasect/core/github.py index 5c3d479..9759164 100644 --- a/src/parasect/core/github.py +++ b/src/parasect/core/github.py @@ -6,6 +6,7 @@ from dotenv import load_dotenv from dataclasses import dataclass from enum import Enum +import re from sqlalchemy.orm import Session @@ -173,14 +174,32 @@ def submit_github_issues(session: Session, protein_to_entry: dict[str, dict[str, submit_github_issue_protein(protein_entry, duplicate_entries, substrates_duplicates, EntryType.DUPLICATE) +def _parse_issue_body_to_json(body: str) -> dict: + """ + Accepts either raw JSON or a Markdown code block containing JSON. + Returns the parsed dict or raises a helpful error. + """ + if not body: + raise ValueError("Empty issue body; nothing to parse.") + + # Try raw JSON first + try: + return json.loads(body) + except json.JSONDecodeError: + pass + + # Try to extract the first fenced code block (```json ... ```) + m = re.search(r"```(?:json)?\s*([\s\S]*?)\s*```", body) + if not m: + raise ValueError("No JSON code block found in issue body.") + json_text = m.group(1) + return json.loads(json_text) + + def fetch_github_issues(token, filter_strings=None, state="all"): """ Fetches all issues from the repo and filters by title content. - - :param token: GitHub personal access token - :param filter_strings: list of substrings to match in the title - :param state: 'open', 'closed', or 'all' - :return: list of matching issue dicts + Excludes pull requests (GitHub returns PRs in the /issues API). """ headers = {"Authorization": f"token {token}"} page = 1 @@ -196,65 +215,89 @@ def fetch_github_issues(token, filter_strings=None, state="all"): if not issues: break # No more pages - if filter_strings: - for issue in issues: - title = issue["title"] - if any(f in title for f in filter_strings): - all_matches.append(issue) - else: - all_matches.extend(issues) + for issue in issues: + # Skip PRs + if "pull_request" in issue: + continue + if not filter_strings or any(f in issue.get("title", "") for f in filter_strings): + all_matches.append(issue) page += 1 return all_matches -def issues_to_files(out_dir: str) -> None: - """Write GitHub issues to folder structure for database processing - - :param out_dir: output directory - :type out_dir: str - """ - keywords = ["New domain entries", "Domain corrections", "Domain sequence revision"] - issues = fetch_github_issues(GITHUB_TOKEN, filter_strings=keywords) - - if issues: - if not os.path.exists(out_dir): - os.mkdir(out_dir) - - for issue in issues: - folder_title = f"issue_{issue['number']}" - issue_folder = os.path.join(out_dir, folder_title) - if not os.path.exists(issue_folder): - os.mkdir(issue_folder) - - data = json.loads(issue["body"]) +def issues_to_files(out_dir: str, keyword: str = None) -> None: + """Write GitHub issues to folder structure for database processing""" + if keyword is None: + keywords = ["New domain entries", + "Domain corrections", + "Domain sequence revision"] + else: + keywords = [keyword] + issues = fetch_github_issues(GITHUB_TOKEN, filter_strings=keywords, state="open") + + if not issues: + return + + os.makedirs(out_dir, exist_ok=True) + + for issue in issues: + folder_title = f"issue_{issue['number']}" + issue_folder = os.path.join(out_dir, folder_title) + os.makedirs(issue_folder, exist_ok=True) + + try: + data = _parse_issue_body_to_json(issue.get("body") or "") + except Exception as e: + raise RuntimeError(f"Failed to parse issue #{issue['number']}: {e}") + + # new_substrates may be absent; default to empty list + new_substrates = data.get("new_substrates", []) or [] + + if new_substrates: + smiles_path = os.path.join(issue_folder, 'smiles.tsv') + with open(smiles_path, 'w') as smiles_out: + smiles_out.write("substrate\tsmiles\n") + for substrate in new_substrates: + smiles_out.write(f"{substrate['name']}\t{substrate['smiles']}\n") + + protein_path = os.path.join(issue_folder, "proteins.fasta") + with open(protein_path, 'w') as protein_out: + protein_out.write(f">{data['protein_name']}\n{data['protein_sequence']}\n") + + domain_path = os.path.join(issue_folder, "domains.fasta") + signature_path = os.path.join(issue_folder, "signatures.fasta") + extended_path = os.path.join(issue_folder, "extended_signatures.fasta") + parasect_path = os.path.join(issue_folder, "parasect_dataset.txt") + smiles_path = os.path.join(issue_folder, "smiles.tsv") + + with open(domain_path, 'w') as domains_out, \ + open(parasect_path, 'w') as parasect_out, \ + open(signature_path, 'w') as signatures_out, \ + open(extended_path, 'w') as extended_out: + + parasect_out.write("domain_id\tsequence\tspecificity\n") + for domain in data["domains"]: + domains_out.write(f">{domain['name']}\n{domain['sequence']}\n") + signatures_out.write(f">{domain['name']}\n{domain['signature']}\n") + extended_out.write(f">{domain['name']}\n{domain['extended_signature']}\n") + parasect_out.write( + f"{domain['name']}\t{domain['sequence']}\t{'|'.join(domain['substrates'])}\n" + ) if data["new_substrates"]: - smiles_path = os.path.join(issue_folder, 'smiles.tsv') with open(smiles_path, 'w') as smiles_out: smiles_out.write("substrate\tsmiles\n") - for substrate in data["new_substrates"]: + for substrate in new_substrates: smiles_out.write(f"{substrate['name']}\t{substrate['smiles']}\n") - protein_path = os.path.join(issue_folder, "proteins.fasta") - with open(protein_path, 'w') as protein_out: - protein_out.write(f">{data['protein_name']}\n{data['protein_sequence']}\n") - - domain_path = os.path.join(issue_folder, "domains.fasta") - signature_path = os.path.join(issue_folder, "signatures.fasta") - extended_path = os.path.join(issue_folder, "extended_signatures.fasta") - parasect_path = os.path.join(issue_folder, "parasect_dataset.txt") - with open(domain_path, 'w') as domains_out, open(parasect_path, 'w') as parasect_out, \ - open(signature_path, 'w') as signatures_out, open(extended_path, 'w') as extended_out: - parasect_out.write("domain_id\tsequence\tspecificity\n") - for domain in data["domains"]: - domains_out.write(f">{domain['name']}\n{domain['sequence']}\n") - signatures_out.write(f">{domain['name']}\n{domain['signature']}\n") - extended_out.write(f">{domain['name']}\n{domain['extended_signature']}\n") - parasect_out.write(f"{domain['name']}\t{domain['sequence']}\t{'|'.join(domain['substrates'])}\n") + + +def fetch_substrate_corrections(out_dir: str): + issues_to_files(out_dir, "Domain corrections") if __name__ == "__main__": - issues_to_files(argv[1]) + fetch_substrate_corrections(argv[1]) From 78e6546b3b10449262f7659ac22bada325e0605d Mon Sep 17 00:00:00 2001 From: "Terlouw, Barbara" Date: Mon, 8 Sep 2025 15:17:15 +0200 Subject: [PATCH 41/65] Cleanup: remove TODO --- src/parasect/database/add_user_submissions.py | 3 --- 1 file changed, 3 deletions(-) diff --git a/src/parasect/database/add_user_submissions.py b/src/parasect/database/add_user_submissions.py index 74794de..6191f1a 100644 --- a/src/parasect/database/add_user_submissions.py +++ b/src/parasect/database/add_user_submissions.py @@ -12,8 +12,6 @@ from parasect.database.populate_database import populate_db # TODO: Refactor such that entries are auto-added as pending to the database -# TODO: Create a table for proteins in the database -# TODO: Create a coordinate field for A-domains in the database def parse_arguments() -> Namespace: @@ -127,7 +125,6 @@ def remap_strings(id_to_string: dict[str, str], mapping: dict[str, str]) -> dict return new_id_to_string -#TODO: Add correction handling def add_user_submissions(submission_dir: str, database_path: str) -> None: """ From 575ca5129b36e06c91475d5079da94fadabf8b86 Mon Sep 17 00:00:00 2001 From: "Terlouw, Barbara" Date: Mon, 8 Sep 2025 15:17:49 +0200 Subject: [PATCH 42/65] Add code to automate database substrate corrections from github issues --- .../database/process_substrate_corrections.py | 87 +++++++++++++++++++ 1 file changed, 87 insertions(+) diff --git a/src/parasect/database/process_substrate_corrections.py b/src/parasect/database/process_substrate_corrections.py index e69de29..1818102 100644 --- a/src/parasect/database/process_substrate_corrections.py +++ b/src/parasect/database/process_substrate_corrections.py @@ -0,0 +1,87 @@ +from argparse import ArgumentParser, Namespace +import os +import traceback + +from sqlalchemy.orm import Session +from sqlalchemy import select, create_engine + +from parasect.database.build_database import Substrate +from parasect.database.query_database import get_domains_from_synonym +from parasect.database.populate_database import create_substrate_entries +from parasect.core.parsing import iterate_over_dir, parse_parasect_data + + +def parse_arguments() -> Namespace: + """Parse arguments from command line + + :return: User-defined arguments + :rtype: Namespace + """ + parser = ArgumentParser(description="Add pending entries to database") + parser.add_argument('-u', type=str, required=True, help="Path to user submissions folder") + parser.add_argument('-db', type=str, required=True, help="Path to PARASECT database") + + args = parser.parse_args() + return args + + +def correct_substrate(session: Session, domain_synonym: str, correct_substrates: list[str]) -> None: + """Correct substrate in database + + :param session: database session + :type session: Session + :param domain_synonym: one synonym for an adenylation domain + :type domain_synonym: str + :param correct_substrates: list of substrates recognised by adenylation domain + :type correct_substrates: list + """ + + domains = get_domains_from_synonym(session, domain_synonym) + if not domains: + raise ValueError(f"No domain found for synonym '{domain_synonym}'") + + domain = domains[0] + + query = select(Substrate).where(Substrate.name.in_(correct_substrates)) + substrates = list(session.scalars(query)) + + missing = set(correct_substrates) - {s.name for s in substrates} + if missing: + raise ValueError(f"Substrates not found in DB: {', '.join(missing)}") + + domain.substrates.clear() + domain.substrates.extend(substrates) + + session.add(domain) + + +def main(): + args = parse_arguments() + engine = create_engine(f"sqlite:///{args.db}") + + with Session(engine) as session: + try: + for _, user_submission_path in iterate_over_dir(args.u, get_dirs=True): + new_substrates = os.path.join(user_submission_path, "smiles.tsv") + if os.path.exists(new_substrates): + + substrates = create_substrate_entries(session, new_substrates) + for substrate in substrates: + session.add(substrate) + + parasect_path = os.path.join(user_submission_path, "parasect_dataset.txt") + _, id_to_spec = parse_parasect_data(parasect_path) + for domain_synonym, substrates in id_to_spec.items(): + correct_substrate(session, domain_synonym, substrates) + + session.commit() + except Exception as e: + print(f"[ERROR] {type(e).__name__}: {e}") + print("Rolling back changes.") + traceback.print_exc() + session.rollback() + finally: + session.close() + +if __name__ == "__main__": + main() From 21ddd7fae0e17625471e0e79d24967c78397e3ca Mon Sep 17 00:00:00 2001 From: "Terlouw, Barbara" Date: Tue, 9 Sep 2025 10:05:31 +0200 Subject: [PATCH 43/65] close #59; Make substrate correction --- app/src/server/parasect.db | Bin 8900608 -> 8900608 bytes 1 file changed, 0 insertions(+), 0 deletions(-) diff --git a/app/src/server/parasect.db b/app/src/server/parasect.db index e1d15c95d0a7ab18d64140f7f84a8c1716d8113c..f5a6dd38f1afa51a24f857fd43dfe68b6d58b6d4 100644 GIT binary patch delta 520 zcmY+=$5N9407YR_fFz=kU^8vBWq=ytd|Y4 zQ8vkD*&*9Fe1POpZ&doRBs-DW~ML zoRPC~PR`2(xhR+9vRsj?a!szw4Y?_me{M;;bjWSVOQ&?n9SP*F+>>s(FFn#L59Fad zl0JDX1$iP*<(WK}7xGeG$!mEdZ>1>xUnzb08BhJ5^lhYSywntF4_p2v9Q;-KQC**j zXQR=eueUp2=m>i9wcpdZa$%wr7AD@k?~1i0M@MQH_z+EwhIQkKKZ#8GV=k8cZ%`f! O1}dx=499|UYv*4MoyqwC delta 489 zcmWO2Nn4Bo0KjomQ_V#7Y=y}lvdgYXk)@Q#8va5VTXtE>^!EPERi`<0z;_tWdvfku z_zI23r324n4!u&`LaM3 z$|6}TOJu3k$}(9lD`cgtk~*oE)v`v`N=h1JovfD)vQak4X4xW*vQ@Upc4?9wvQu`+ zZrLMyWuNSqW;q}S<&YefBXU%Z$#H3sw6w|zX_Iz2DW{}EPRkiNE9azBy5zicOOITT zUb!fjq)#r(6}c+c Date: Sun, 14 Sep 2025 16:00:34 +0200 Subject: [PATCH 44/65] Add train test splitting on taxonomic rank --- .../data_preparation/__init__.py | 0 .../data_preparation/taxonomy/__init__.py | 0 .../train_test_splits/__init__.py | 0 .../train_test_splits/split_on_rank.py | 525 +++++ model_training/pca/__init__.py | 0 model_training/pca/apply_pca.py | 0 .../train => model_training}/pca/build_pca.py | 0 model_training/rf/__init__.py | 0 .../train => model_training}/rf/train_rf.py | 0 src/parasect/data/database_files/taxonomy.txt | 1696 +++++++++++++++++ src/parasect/database/protein_identifiers.py | 0 11 files changed, 2221 insertions(+) rename src/parasect/train/pca/apply_pca.py => model_training/data_preparation/__init__.py (100%) create mode 100644 model_training/data_preparation/taxonomy/__init__.py create mode 100644 model_training/data_preparation/train_test_splits/__init__.py create mode 100644 model_training/data_preparation/train_test_splits/split_on_rank.py create mode 100644 model_training/pca/__init__.py create mode 100644 model_training/pca/apply_pca.py rename {src/parasect/train => model_training}/pca/build_pca.py (100%) create mode 100644 model_training/rf/__init__.py rename {src/parasect/train => model_training}/rf/train_rf.py (100%) create mode 100644 src/parasect/data/database_files/taxonomy.txt create mode 100644 src/parasect/database/protein_identifiers.py diff --git a/src/parasect/train/pca/apply_pca.py b/model_training/data_preparation/__init__.py similarity index 100% rename from src/parasect/train/pca/apply_pca.py rename to model_training/data_preparation/__init__.py diff --git a/model_training/data_preparation/taxonomy/__init__.py b/model_training/data_preparation/taxonomy/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/model_training/data_preparation/train_test_splits/__init__.py b/model_training/data_preparation/train_test_splits/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/model_training/data_preparation/train_test_splits/split_on_rank.py b/model_training/data_preparation/train_test_splits/split_on_rank.py new file mode 100644 index 0000000..b9cd7f9 --- /dev/null +++ b/model_training/data_preparation/train_test_splits/split_on_rank.py @@ -0,0 +1,525 @@ +import random +import os +from typing import Optional, Iterable +from argparse import ArgumentParser, Namespace +from enum import Enum + +from sqlalchemy.orm import Session +from sqlalchemy import create_engine, select + +from parasect.database.build_database import AdenylationDomain, Taxonomy, Substrate + + +def parse_arguments() -> Namespace: + """Parse arguments from command line + + :return: Arguments + :rtype: Namespace + """ + parser = ArgumentParser(description="Retrieve taxonomy for database domains") + + parser.add_argument("-db", "--database", type=str, required=True, + help="Path to PARASECT database") + parser.add_argument("-o", "--output", required=True, type=str, + help="Output directory") + parser.add_argument("-f", '--first_only', action="store_true", + help="If given, only consider first listed substrate for each domain.") + parser.add_argument("-c", '--cutoff', default=6, type=int, + help="Minimum substrate count for inclusion") + parser.add_argument("-r", '--test_ratio', default=0.25, type=float, + help="Target test set size") + parser.add_argument("-m", '--max_attempts', default=200, + help="Max attempts made for splitting data") + parser.add_argument("-t", "--taxonomic_rank", default="family", type=str, + help="Taxonomic rank to split on") + + arguments = parser.parse_args() + + return arguments + + +class SplitMode(Enum): + FIRST_ONLY = 1 + FIRST_VALID = 2 + ALL = 3 + + @staticmethod + def get_mode_from_string(string) -> "SplitMode": + string_to_split_mode = {s.name: s for s in SplitMode} + return string_to_split_mode.get(string.upper()) + + +class Rank(Enum): + DOMAIN = 1 + KINGDOM = 2 + PHYLUM = 3 + CLASS = 4 + ORDER = 5 + FAMILY = 6 + GENUS = 7 + SPECIES = 8 + STRAIN = 9 + + @staticmethod + def get_rank_from_taxonomy(rank: "Rank", taxonomy: Taxonomy) -> Optional[str]: + """ + Return specific rank from full taxonomy + :param rank: taxonomic rank + :type rank: Rank + :param taxonomy: taxonomy from database + :type taxonomy: Taxonomy + :return: string representing taxonomic rank, None if not in database + :rtype: str or None + """ + rank_to_value = {Rank.DOMAIN: taxonomy.domain, + Rank.KINGDOM: taxonomy.kingdom, + Rank.PHYLUM: taxonomy.phylum, + Rank.CLASS: taxonomy.cls, + Rank.ORDER: taxonomy.order, + Rank.FAMILY: taxonomy.family, + Rank.GENUS: taxonomy.genus, + Rank.SPECIES: taxonomy.species, + Rank.STRAIN: taxonomy.strain} + + return rank_to_value[rank] + + @staticmethod + def get_rank_type_from_string(string: str) -> "Rank": + string_to_rank_type = {r.name: r for r in Rank} + return string_to_rank_type.get(string.upper()) + + +def _count_first_valid_substrate(domains: Iterable[AdenylationDomain], cutoff: int): + # Step 1: start with all substrates meeting cutoff globally + global_counts = _count_substrates_in_domains(domains, first_only=False) + valid_substrates = {s for s, c in global_counts.items() if c >= cutoff} + + changed = True + domain_to_valid = {} + counts = {} + + while changed: + # Step 2: assign first valid substrate for each domain + domain_to_valid = {} + counts = {s: 0 for s in valid_substrates} + for d in domains: + for s in d.substrates: + if s in valid_substrates: + domain_to_valid[d] = s + counts[s] += 1 + break + else: + # No valid substrate for this domain + domain_to_valid[d] = None + + # Step 3: prune those that fell below cutoff + demoted = {s for s, c in counts.items() if c < cutoff} + if demoted: + valid_substrates -= demoted + changed = True + else: + changed = False + + return counts + + +def get_clades(session: Session, rank: Rank) -> dict[tuple[str, ...], set[AdenylationDomain]]: + """Return mapping of a group of clades of a certain rank to the domains belonging to that group + + :param session: database session + :type session: Session + :param rank: taxonomic rank + :type rank: Rank + :return: dictionary mapping clade groups (e.g. (Burkholderiaceae, Pseudomonadaceae) to domains + :rtype: dict[tuple[str, ...], set[AdenylationDomain]] + """ + # Clade grouping is necessary because it is possible that a single domain sequence maps to multiple proteins that + # belong to different taxonomic lineages. E.g., domain ADH01485.1.A1|AIC32693.1.A1 belongs to both the + # Burkholderiaceae (ADH01485.1.A1) and the Pseudomonadaceae (AIC32693.1.A1) families + + domains = list(session.scalars(select(AdenylationDomain)).all()) + clade_to_domains: dict[str, set[AdenylationDomain]] = {} + clade_to_clade_group: dict[str, set[str]] = {} + for domain in domains: + clades = set() + for protein in [p.protein for p in domain.proteins]: + clades.add(Rank.get_rank_from_taxonomy(rank, protein.taxonomy)) + + for clade in clades: + + # Set aliasing ensures updates across all clades + if clade in clade_to_clade_group: + clade_to_clade_group[clade].update(clades) + clades = clade_to_clade_group[clade] + + else: + clade_to_clade_group[clade] = clades + + clade_to_domains.setdefault(clade, set()).add(domain) + + # Collapse into groups: tuple of clades → set of domains + clade_group_to_domains: dict[tuple[str, ...], set[AdenylationDomain]] = {} + + for clade, domains_in_clade in clade_to_domains.items(): + group = clade_to_clade_group[clade] + group_key = tuple(sorted(group)) + clade_group_to_domains.setdefault(group_key, set()).update(domains_in_clade) + + return clade_group_to_domains + + +def _count_substrates_in_domains(domains: Iterable[AdenylationDomain], + first_only: bool) -> dict[Substrate, int]: + """Count substrate specificities of domains + + :param domains: collection of unique adenylation domains + :type domains: Iterable[AdenylationDomain] + :param first_only: if True, only count the first substrate for each domain. + :type first_only: bool + :return: dictionary mapping substrate to substrate counts + :rtype: dict[Substrate, int] + """ + counts: dict[Substrate, int] = {} + + for domain in domains: + for substrate in domain.substrates: + if substrate not in counts: + counts[substrate] = 0 + counts[substrate] += 1 + + if first_only: + break + + return counts + + +def count_substrates(session: Session, first_only: bool, cutoff: int = 0) -> dict[Substrate, int]: + """Count substrate occurrences in database + + :param session: database session + :type session: Session + :param first_only: if given, only count the first substrate for each domain + :type first_only: bool + :param cutoff: only include substrates that occur at least this many times + :type cutoff: int + :return: dictionary mapping substrate to substrate counts + :rtype: dict[Substrate, int] + """ + domains = list(session.scalars(select(AdenylationDomain)).all()) + substrate_to_count = _count_substrates_in_domains(domains, first_only) + + for substrate, count in list(substrate_to_count.items()): + if count < cutoff: + del substrate_to_count[substrate] + + return substrate_to_count + + +def get_counts_per_clade(clade_group_to_domains: dict[tuple[str, ...], set[AdenylationDomain]], + included_substrates: set[Substrate], + first_only: bool) -> dict[tuple[str, ...], dict[Substrate, int]]: + """Return dictionary recording substrate counts for each clade + + :param clade_group_to_domains: dictionary mapping clade groups to domains + :type clade_group_to_domains: dict[tuple[str, ...], set[AdenylationDomain]] + :param included_substrates: set of included substrates + :type included_substrates: set[Substrate] + :param first_only: if given, only record the first substrate in the list + :type first_only: bool + :return: dictionary recording substrate counts for each clade + :rtype: dict[tuple[str, ...], dict[Substrate, int]] + """ + counts_per_clade: dict[tuple[str, ...], dict[Substrate, int]] = {} + + for clade, domains in clade_group_to_domains.items(): + substrate_to_count = _count_substrates_in_domains(domains, first_only=first_only) + for substrate in list(substrate_to_count.keys()): + if substrate not in included_substrates: + del substrate_to_count[substrate] + + counts_per_clade[clade] = substrate_to_count + + return counts_per_clade + + +def split_on_rank(session: Session, + rank: Rank, + cutoff: int = 6, + target_ratio: float = 0.75, + first_only: bool = True, + max_attempts: int = 200) -> dict[str, dict]: + """Split dataset into phylogenetically distinct train and test set based on taxonomic rank + + :param session: database session + :type session: Session + :param rank: taxonomic rank to split on (e.g. if 'family', domains of the same family will be assigned + to either train or test but not both + :type rank: Rank + :param cutoff: only consider substrates that occur at least this many times in the dataset + :type cutoff: int + :param target_ratio: target ratio of datapoints in training set + :type target_ratio: float + :param first_only: if True, consider only the first listed subsrate for each domain. Default: True + :type first_only: bool + :param max_attempts: maximum number of attempts to try splitting the dataset. Default: 200 + :type max_attempts: int + :return: dictionary containing clade mappings (assignment) and substrate counts + :rtype: dict[str, dict] + """ + rng = random.Random(100125) + substrate_to_count = count_substrates(session, first_only, cutoff) + substrates = list(substrate_to_count.keys()) + substrates.sort(key=lambda x: x.name) + grouped_clades = get_clades(session, rank) + clade_substrate_counts = get_counts_per_clade(grouped_clades, set(substrate_to_count.keys()), first_only) + + # coverage phase: ensure each substrate occurs in both train and test set + def try_build_coverage(): + assignment = {} + for substrate in rng.sample(substrates, len(substrates)): + clades_with_substrate = [c for c, counts in clade_substrate_counts.items() if counts.get(substrate, 0) > 0] + assigned_train = any(assignment.get(c) == "train" for c in clades_with_substrate) + assigned_test = any(assignment.get(c) == "test" for c in clades_with_substrate) + + if assigned_train and assigned_test: + continue + + if not assigned_train and not assigned_test: + if len(clades_with_substrate) < 2: + return None + c1, c2 = rng.sample(clades_with_substrate, 2) + assignment[c1] = "train" + assignment[c2] = "test" + + elif assigned_train and not assigned_test: + unassigned = [c for c in clades_with_substrate if c not in assignment] + if not unassigned: + return None + assignment[unassigned[0]] = "test" + + elif assigned_test and not assigned_train: + unassigned = [c for c in clades_with_substrate if c not in assignment] + if not unassigned: + return None + assignment[unassigned[0]] = "train" + + return assignment + + coverage_assignment = None + for _ in range(max_attempts): + coverage_assignment = try_build_coverage() + if coverage_assignment: + break + if not coverage_assignment: + raise RuntimeError("Could not satisfy coverage constraints.") + + # initialize substrate counts + substrate_counts = {s: {"train": 0, "test": 0} for s in substrates} + for clade, side in coverage_assignment.items(): + for sub, cnt in clade_substrate_counts[clade].items(): + substrate_counts[sub][side] += cnt + + # assign remaining clades greedily + unassigned = [c for c in clade_substrate_counts if c not in coverage_assignment] + unassigned.sort(key=lambda c: -sum(clade_substrate_counts[c].values())) + + def total_error(counts): + err = 0.0 + for sub, ct in counts.items(): + total = ct["train"] + ct["test"] + if total == 0: + continue + desired = total * target_ratio + err += (ct["train"] - desired) ** 2 + return err + + for clade in unassigned: + best_side, best_err = None, None + for side in ("train", "test"): + temp = {s: ct.copy() for s, ct in substrate_counts.items()} + for sub, cnt in clade_substrate_counts[clade].items(): + temp[sub][side] += cnt + err = total_error(temp) + if best_err is None or err < best_err: + best_side, best_err = side, err + coverage_assignment[clade] = best_side + for sub, cnt in clade_substrate_counts[clade].items(): + substrate_counts[sub][best_side] += cnt + + # sanity check + for sub, ct in substrate_counts.items(): + if ct["train"] == 0 or ct["test"] == 0: + raise RuntimeError(f"Substrate {sub} missing from one split") + + domain_assignment: dict[AdenylationDomain, str] = {} + for clade, side in coverage_assignment.items(): + for domain in grouped_clades[clade]: + if domain in domain_assignment: + raise RuntimeError( + f"Domain {domain} assigned twice " + f"({domain_assignment[domain]} and {side})" + ) + if first_only: + if domain.substrates[0] in substrates: + domain_assignment[domain] = side + else: + if any(sub in substrates for sub in domain.substrates): + domain_assignment[domain] = side + + return { + "assignment": coverage_assignment, + "substrate_counts": substrate_counts, + "domain_assignment": domain_assignment + } + + +def main(): + args = parse_arguments() + engine = create_engine(f"sqlite:///{args.database}") + if not os.path.exists(args.output): + os.mkdir(args.output) + + train_clades_out = os.path.join(args.output, "train_clades.txt") + test_clades_out = os.path.join(args.output, "test_clades.txt") + + train_out = os.path.join(args.output, "train.txt") + test_out = os.path.join(args.output, "test.txt") + + substrate_splits = os.path.join(args.output, "substrate_splits.txt") + + with Session(engine) as session: + rank_type = Rank.get_rank_type_from_string(args.taxonomic_rank) + result = split_on_rank(session, rank_type, + cutoff=args.cutoff, + target_ratio=1.0 - args.test_ratio, + first_only=args.first_only, + max_attempts=args.max_attempts) + + clade_assignment = result["assignment"] + substrate_counts = result["substrate_counts"] + domain_assignment = result["domain_assignment"] + + with open(train_out, 'w') as train, open(test_out, 'w') as test: + for domain, assignment in domain_assignment.items(): + if assignment == "train": + train.write(f"{domain.get_name()}\n") + elif assignment == "test": + test.write(f"{domain.get_name()}\n") + else: + raise ValueError(f"Unknown domain assignment: {assignment}") + + with open(train_clades_out, 'w') as train_clades, open(test_clades_out, 'w') as test_clades: + for clades, assignment in clade_assignment.items(): + for clade in clades: + if assignment == "train": + train_clades.write(f"{clade}\n") + elif assignment == "test": + test_clades.write(f"{clade}\n") + else: + raise ValueError(f"Unknown clade assignment: {assignment}") + + with open(substrate_splits, 'w') as substrates_out: + substrates_out.write("substrate_name\ttrain\ttest\n") + for substrate, counts in substrate_counts.items(): + substrates_out.write(f"{substrate.name}\t{counts['train']}\t{counts['test']}\n") + + # Sum across all substrates + total_train = sum(ct["train"] for ct in substrate_counts.values()) + total_test = sum(ct["test"] for ct in substrate_counts.values()) + + print(f"Total domains in train: {total_train}") + print(f"Total domains in test: {total_test}") + + if args.first_only: + num_train_domains = sum(1 for side in domain_assignment.values() if side == "train") + num_test_domains = sum(1 for side in domain_assignment.values() if side == "test") + + total_counts = total_train + total_test + num_domains = len(domain_assignment) + + # Check totals + if total_counts != num_domains: + raise RuntimeError( + f"Sanity check failed: {total_counts} substrate counts but " + f"{num_domains} domains assigned (expected equality with first_only=True)." + ) + + # Check per-split counts + if total_train != num_train_domains: + raise RuntimeError( + f"Sanity check failed: train substrate count ({total_train}) " + f"!= number of train domains ({num_train_domains})." + ) + + if total_test != num_test_domains: + raise RuntimeError( + f"Sanity check failed: test substrate count ({total_test}) " + f"!= number of test domains ({num_test_domains})." + ) + else: + # 1. No domain assigned twice + assigned_domains = set() + for domain, side in domain_assignment.items(): + if domain in assigned_domains: + raise RuntimeError(f"Domain {domain} assigned twice") + assigned_domains.add(domain) + + # 2. Every substrate counted is on the side of some domain + for sub, counts in substrate_counts.items(): + counted_train = sum(1 for d, side in domain_assignment.items() + if side == "train" and sub in d.substrates) + counted_test = sum(1 for d, side in domain_assignment.items() + if side == "test" and sub in d.substrates) + + if counted_train != counts["train"]: + raise RuntimeError( + f"Mismatch for substrate {sub}: train counted {counts['train']}, " + f"sum over domains {counted_train}" + ) + if counted_test != counts["test"]: + raise RuntimeError( + f"Mismatch for substrate {sub}: test counted {counts['test']}, " + f"sum over domains {counted_test}" + ) + + # Get all domains that have at least one substrate in the counted list + legal_domains = set() + for domain in session.scalars(select(AdenylationDomain)).all(): + if any(sub in substrate_counts for sub in domain.substrates): + legal_domains.add(domain) + + # Compare with assigned domains + assigned_domains = set(domain_assignment.keys()) + + missing = legal_domains - assigned_domains + extra = assigned_domains - legal_domains + + if missing or extra: + raise RuntimeError( + f"Domain assignment mismatch: " + f"{len(missing)} legal domains missing, " + f"{len(extra)} extra domains assigned" + ) + + test_substrates = set() + train_substrates = set() + for domain, assignment in domain_assignment.items(): + first_valid_substrate = None + for substrate in domain.substrates: + if substrate in substrate_counts: + first_valid_substrate = substrate + break + assert first_valid_substrate is not None + if assignment == 'test': + test_substrates.add(first_valid_substrate) + elif assignment == 'train': + train_substrates.add(first_valid_substrate) + + if train_substrates != test_substrates: + for substrate in train_substrates ^ test_substrates: + print(substrate_counts[substrate]) + print(train_substrates - test_substrates) + + +if __name__ == "__main__": + main() diff --git a/model_training/pca/__init__.py b/model_training/pca/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/model_training/pca/apply_pca.py b/model_training/pca/apply_pca.py new file mode 100644 index 0000000..e69de29 diff --git a/src/parasect/train/pca/build_pca.py b/model_training/pca/build_pca.py similarity index 100% rename from src/parasect/train/pca/build_pca.py rename to model_training/pca/build_pca.py diff --git a/model_training/rf/__init__.py b/model_training/rf/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/src/parasect/train/rf/train_rf.py b/model_training/rf/train_rf.py similarity index 100% rename from src/parasect/train/rf/train_rf.py rename to model_training/rf/train_rf.py diff --git a/src/parasect/data/database_files/taxonomy.txt b/src/parasect/data/database_files/taxonomy.txt new file mode 100644 index 0000000..2c62d05 --- /dev/null +++ b/src/parasect/data/database_files/taxonomy.txt @@ -0,0 +1,1696 @@ +protein_id domain kingdom phylum class order family genus species strain +A05163 Eukaryota Metazoa Chordata Craniata Perciformes Cottidae Myoxocephalus Myoxocephalus scorpius Unknown +A0FCL0 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces violaceusniger Unknown +A45086 Eukaryota Fungi Ascomycota Dothideomycetes Pleosporales Pleosporaceae Bipolaris Bipolaris zeicola Unknown +A6P624 Bacteria Bacillati Cyanobacteriota Cyanophyceae Chroococcales Microcystaceae Microcystis Microcystis aeruginosa K-139 +A8BB73 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Lysobacterales Lysobacteraceae Lysobacter Lysobacter enzymogenes C3 +A8KCJ2 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Sphaerotilaceae Caldimonas Caldimonas brevitalea DSM 7029 +AAA03914.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus nidulans Unknown +AAA25234.1 Bacteria Bacillati Bacillota Bacilli Lactobacillales Lactobacillaceae Lacticaseibacillus Lacticaseibacillus casei Unknown +AAA27636.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Yersiniaceae Yersinia Yersinia enterocolitica Ye 8081 +AAA33023.2 Eukaryota Fungi Ascomycota Dothideomycetes Pleosporales Pleosporaceae Bipolaris Bipolaris zeicola SB111 +AAA34747.1 Eukaryota Fungi Ascomycota Saccharomycetes Saccharomycetales Saccharomycetaceae Saccharomyces Saccharomyces cerevisiae S288C +AAA63415.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Penicillium Penicillium chrysogenum ASP-78 +AAA92015.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Enterobacteriaceae Escherichia Escherichia coli Unknown +AAA93464.1|Q56950 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Yersiniaceae Yersinia Yersinia pestis Unknown +AAB00093.1|Q45563 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus subtilis Unknown +AAB39900.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces clavuligerus Unknown +AAB60198.1|Q51338 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas aeruginosa Unknown +AAB80955.2|O30980 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus subtilis Unknown +AAB80956.1|O30981 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus subtilis Unknown +AAB93493.1 Eukaryota Fungi Basidiomycota Ustilaginomycetes Ustilaginales Ustilaginaceae Mycosarcoma Mycosarcoma maydis Unknown +AAC05774.1|Q53526.4 Bacteria Bacillati Bacillota Bacilli Lactobacillales Streptococcaceae Streptococcus Streptococcus mutans UA159 Unknown +AAC06346.1 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus licheniformis ATCC 10716 +AAC06347.1 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus licheniformis ATCC 10716 +AAC06348.1 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus licheniformis ATCC 10716 +AAC36721.1|O87606 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus subtilis Unknown +AAC44128.1|Q50857 Bacteria Pseudomonadati Pseudomonadota Deltaproteobacteria Myxococcales Myxococcaceae Myxococcus Myxococcus xanthus Unknown +AAC44129.1|Q50858 Bacteria Pseudomonadati Pseudomonadota Deltaproteobacteria Myxococcales Myxococcaceae Myxococcus Myxococcus xanthus Unknown +AAC44632.1|CAB15188.1|P40871.2 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus subtilis subsp. subtilis str. 168 +AAC45929.1 Bacteria Bacillati Bacillota Bacilli Bacillales Paenibacillaceae Brevibacillus Brevibacillus brevis ATCC 8185 +AAC68816.1|Q9ZGA6 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. MA6548 Unknown +AAC80285.1|O85168 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas syringae pv. syringae Unknown +AAC82549.1|O87313 Bacteria Bacillati Actinomycetota Actinomycetes Mycobacteriales Mycobacteriaceae Mycolicibacterium Mycolicibacterium smegmatis Unknown +AAC82550.1|O87314 Bacteria Bacillati Actinomycetota Actinomycetes Mycobacteriales Mycobacteriaceae Mycolicibacterium Mycolicibacterium smegmatis Unknown +AAC83656.1|O85739 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas aeruginosa Unknown +AAC83657.1|O85740 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas aeruginosa Unknown +AAD04757.1|O66069 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus licheniformis Unknown +AAD04759.1|O66071 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus licheniformis Unknown +AAD44233.1 Bacteria Bacillati Actinomycetota Actinomycetes Mycobacteriales Mycobacteriaceae Mycobacterium Mycobacterium avium 2151 +AAD44234.1 Bacteria Bacillati Actinomycetota Actinomycetes Mycobacteriales Mycobacteriaceae Mycobacterium Mycobacterium avium 2151 +AAD50521.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas syringae pv. syringae B301D +AAD55799.1|Q9RFM9 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas aeruginosa Unknown +AAD56240.1 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus subtilis MR 168 +AAF00957.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Chroococcales Microcystaceae Microcystis Microcystis aeruginosa PCC 7806 +AAF00958.1|Q9RNB3 Bacteria Bacillati Cyanobacteriota Cyanophyceae Chroococcales Microcystaceae Microcystis Microcystis aeruginosa PCC 7806 Unknown +AAF00960.1|Q9RNB1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Chroococcales Microcystaceae Microcystis Microcystis aeruginosa PCC 7806 Unknown +AAF00961.1|Q9RNB0 Bacteria Bacillati Cyanobacteriota Cyanophyceae Chroococcales Microcystaceae Microcystis Microcystis aeruginosa PCC 7806 Unknown +AAF00962.1|Q9RNA9 Bacteria Bacillati Cyanobacteriota Cyanophyceae Chroococcales Microcystaceae Microcystis Microcystis aeruginosa PCC 7806 Unknown +AAF01762.1 Eukaryota Fungi Ascomycota Dothideomycetes Pleosporales Pleosporaceae Alternaria Alternaria alternata M-71 +AAF08795.1 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus spizizenii ATCC 6633 = JCM 2499 ATCC 6633 +AAF08796.1|Q9R9J0.1 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus spizizenii ATCC 6633 = JCM 2499 ATCC 6633 +AAF08797.1|Q9R9I9.1 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus spizizenii ATCC 6633 = JCM 2499 ATCC 6633 +AAF15891.2|Q9RAH4 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Nostocaceae Nostoc Nostoc sp. GSV224 Unknown +AAF17280.1|Q9RAH2 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Nostocaceae Nostoc Nostoc sp. GSV224 Unknown +AAF17281.1|Q9RAH1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Nostocaceae Nostoc Nostoc sp. GSV224 Unknown +AAF19811.1 Bacteria Pseudomonadati Myxococcota Myxococcia Myxococcales Archangiaceae Stigmatella Stigmatella aurantiaca DW4/3-1 +AAF19812.1|Q9RFK8 Bacteria Pseudomonadati Pseudomonadota Deltaproteobacteria Myxococcales Archangiaceae Stigmatella Stigmatella aurantiaca Unknown +AAF19815.1 Bacteria Pseudomonadati Myxococcota Myxococcia Myxococcales Archangiaceae Stigmatella Stigmatella aurantiaca DW4/3-1 +AAF62881.1 Bacteria Pseudomonadati Myxococcota Polyangia Polyangiales Polyangiaceae Sorangium Sorangium cellulosum SMP44 +AAF86395.1|Q9KID8 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces hygroscopicus subsp. ascomyceticus Unknown +AAF99707.2|Q9FDB3 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas syringae pv. syringae Unknown +AAG00564.1|Q9FDB2 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Vibrionales Vibrionaceae Vibrio Vibrio cholerae Unknown +AAG00566.1|Q9FDB0 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Vibrionales Vibrionaceae Vibrio Vibrio cholerae Unknown +AAG02355.1|Q9FB27 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces verticillus Unknown +AAG02356.1|Q9FB26 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces verticillus Unknown +AAG02358.1|Q9FB24 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces verticillus Unknown +AAG02359.1|Q9FB23 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces verticillus Unknown +AAG02364.1|Q9FB18 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces verticillus Unknown +AAG02365.1|Q9FB17 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces verticillus Unknown +AAG05812.1|Q9I157 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas aeruginosa Unknown +AAG06715.1|NP_252017.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas aeruginosa PAO1 +AAG31128.1 Bacteria Pseudomonadati Myxococcota Myxococcia Myxococcales Archangiaceae Stigmatella Stigmatella aurantiaca Sg a15 +AAG31130.1 Bacteria Pseudomonadati Myxococcota Myxococcia Myxococcales Archangiaceae Stigmatella Stigmatella aurantiaca Sg a15 +AAK21902.1|Q9C1G0 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Bionectriaceae Kallichroma Kallichroma tethys Unknown +AAK46746.1 Bacteria Bacillati Actinomycetota Actinomycetes Mycobacteriales Mycobacteriaceae Mycobacterium Mycobacterium tuberculosis CDC1551 +AAK57184.1 Bacteria Pseudomonadati Myxococcota Myxococcia Myxococcales Archangiaceae Stigmatella Stigmatella aurantiaca Unknown +AAK76230.1 Bacteria Bacillati Bacillota Bacilli Lactobacillales Streptococcaceae Streptococcus Streptococcus pneumoniae TIGR4 TIGR4; ATCC BAA-334 +AAK81824.1|Q93N89 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces lavendulae Unknown +AAK81825.1|Q93N88 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces lavendulae Unknown +AAK81826.1|Q93N87 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces lavendulae Unknown +AAK81827.1|Q93N86 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces lavendulae Unknown +AAL33756.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas fluorescens A2-2 +AAL33757.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas fluorescens A2-2 +AAL33758.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas fluorescens A2-2 +AAL82383.1|Q8RTG4 Bacteria Bacillati Cyanobacteriota Cyanophyceae Chroococcales Microcystaceae Microcystis Microcystis aeruginosa Unknown +AAM78457.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Hypocreaceae Trichoderma Trichoderma virens Unknown +AAM80536.1|Q8KLL6 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces toyocaensis Unknown +AAM80537.1|Q8KLL5 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces toyocaensis Unknown +AAM80538.1|Q8KLL4 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces toyocaensis Unknown +AAM80539.1|Q8KLL3 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces toyocaensis Unknown +AAN00653.1 Bacteria Bacillati Bacillota Bacilli Lactobacillales Streptococcaceae Streptococcus Streptococcus agalactiae 2603V/R +AAN07012.1 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus subtilis ATTCAU195 +AAN07013.1 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus subtilis ATTCAU195 +AAN07014.1 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus subtilis ATTCAU195 +AAN32978.1|Q8GAQ6 Bacteria Bacillati Cyanobacteriota Cyanophyceae Oscillatoriales Microcoleaceae Lyngbya Lyngbya majuscula Unknown +AAN32981.1|Q8GAQ3 Bacteria Bacillati Cyanobacteriota Cyanophyceae Oscillatoriales Microcoleaceae Lyngbya Lyngbya majuscula Unknown +AAN42148.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Enterobacteriaceae Shigella Shigella flexneri 2a str. 301 +AAN74813.2 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Nectriaceae Fusarium Fusarium fujikuroi var. moniliformis M-3125 +AAN85522.1|Q8GGP3 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces atroolivaceus Unknown +AAN85530.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces atroolivaceus Unknown +AAO07759.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Vibrionales Vibrionaceae Vibrio Vibrio vulnificus CMCP6 +AAO07763.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Vibrionales Vibrionaceae Vibrio Vibrio vulnificus CMCP6 +AAO23333.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Nostocaceae Nostoc Nostoc sp. ATCC 53789 +AAO23334.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Nostocaceae Nostoc Nostoc sp. ATCC 53789 +AAO55665.1|Q884E5 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas syringae pv. tomato Unknown +AAO55666.1|Q884E4 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas syringae pv. tomato Unknown +AAO55667.1|Q884E3 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas syringae pv. tomato Unknown +AAO56328.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas syringae pv. tomato str. DC3000 +AAO56329.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas syringae pv. tomato str. DC3000 +AAO62582.1|Q7WRI6 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Nostocaceae Anabaena Anabaena sp. 90 Unknown +AAO62585.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Nostocaceae Anabaena Anabaena sp. 90 Unknown +AAO62586.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Nostocaceae Anabaena Anabaena sp. 90 Unknown +AAO62587.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Nostocaceae Anabaena Anabaena sp. 90 Unknown +AAO62588.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Nostocaceae Anabaena Anabaena sp. 90 Unknown +AAO64403.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Nodulariaceae Nodularia Nodularia spumigena NSOR10 +AAO69874.1|Q8Z8L1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Enterobacteriaceae Salmonella Salmonella enterica subsp. enterica serovar Typhi Unknown +AAO72424.1|Q83VS1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas syringae pv. syringae Unknown +AAO72425.1|Q83VS0 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas syringae pv. syringae Unknown +AAO92378.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Vibrionales Vibrionaceae Vibrio Vibrio anguillarum Unknown +AAP56239.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus nidulans Unknown +AAP92491.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces vinaceus ATCC 11861 +AAP92505.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces vinaceus ATCC 11861 +AAQ82561.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. FR-008 Unknown +AAQ93484.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas savastanoi pv. glycinea PG4180 +AAS47562.1 Bacteria None None None None None None symbiont bacterium of Paederus fuscipes Unknown +AAS47564.1 Bacteria None None None None None None symbiont bacterium of Paederus fuscipes Unknown +AAS92545.1 Eukaryota Fungi Ascomycota Dothideomycetes Pleosporales Leptosphaeriaceae Plenodomus Plenodomus lingam Unknown +AAS98786.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Oscillatoriales Microcoleaceae Lyngbya Lyngbya majuscula JHB +AAT01806.1 Bacteria Bacillati Actinomycetota Actinomycetes Mycobacteriales Mycobacteriaceae Mycolicibacterium Mycolicibacterium smegmatis MC2 155 +AAT01807.1 Bacteria Bacillati Actinomycetota Actinomycetes Mycobacteriales Mycobacteriaceae Mycolicibacterium Mycolicibacterium smegmatis MC2 155 +AAT09804.1 Bacteria Bacillati Actinomycetota Actinomycetes Mycobacteriales Nocardiaceae Nocardia Nocardia uniformis subsp. tsuyamanensis ATCC 21806 +AAT09805.1 Bacteria Bacillati Actinomycetota Actinomycetes Mycobacteriales Nocardiaceae Nocardia Nocardia uniformis subsp. tsuyamanensis ATCC 21806 +AAT12283.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Oscillatoriales Microcoleaceae Lyngbya Lyngbya majuscula Unknown +AAT28740.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Nectriaceae Fusarium Fusarium verticillioides Unknown +AAT70101.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Oscillatoriales Microcoleaceae Lyngbya Lyngbya majuscula 19L +AAU22002.1|AAU39359.1 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus licheniformis DSM 13 = ATCC 14580 DSM 13 +AAU34202.1|Q643C7 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces hygroscopicus Unknown +AAU34203.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces hygroscopicus Unknown +AAU39360.1 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus licheniformis DSM 13 = ATCC 14580 DSM 13 +AAV66110.2 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Nectriaceae Fusarium Fusarium heterosporum ATCC 74349 +AAV97877.1 Bacteria None None None None None None symbiont bacterium of Theonella swinhoei Unknown +AAW03307.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus fumigatus Unknown +AAW03326.1 Bacteria Pseudomonadati Myxococcota Myxococcia Myxococcales Archangiaceae Cystobacter Cystobacter fuscus Unknown +AAX16296.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas aeruginosa 10-15 +AAX16297.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas aeruginosa 10-15 +AAX16325.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas aeruginosa 206-12 +AAX16327.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas aeruginosa 206-12 +AAX31557.1|Q50E74 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces filamentosus Unknown +AAX31558.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces filamentosus NRRL 11379 +AAX31559.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces filamentosus NRRL 11379 +AAX73195.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Chroococcales Microcystaceae Microcystis Microcystis aeruginosa PCC 7820 +AAY29578.1 Bacteria Bacillati Bacillota Bacilli Bacillales Paenibacillaceae Brevibacillus Brevibacillus texasporus ATCC PTA-5854 +AAY29580.1 Bacteria Bacillati Bacillota Bacilli Bacillales Paenibacillaceae Brevibacillus Brevibacillus texasporus ATCC PTA-5854 +AAY37647.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas syringae pv. syringae B728a +AAY37650.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas syringae pv. syringae B728a +AAY42397.1|Q1EDB1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Oscillatoriales Microcoleaceae Lyngbya Lyngbya majuscula Unknown +AAY42398.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Oscillatoriales Microcoleaceae Lyngbya Lyngbya majuscula Unknown +AAY89051.1|Q2N3S9 Bacteria Pseudomonadati Pseudomonadota Deltaproteobacteria Myxococcales Polyangiaceae Sorangium Sorangium cellulosum Unknown +AAY91419.3 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas protegens Pf-5 +AAY91420.2 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas protegens Pf-5 +AAY91421.3 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas protegens Pf-5 +AAY93354.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas protegens Pf-5 +AAY93355.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas protegens Pf-5 +AAY93356.2 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas protegens Pf-5 +AAY93445.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas protegens Pf-5 +AAZ03550.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Chroococcales Microcystaceae Microcystis Microcystis sp. NIVA-CYA 172/5 +AAZ03551.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Chroococcales Microcystaceae Microcystis Microcystis sp. NIVA-CYA 172/5 +AAZ03552.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Chroococcales Microcystaceae Microcystis Microcystis sp. NIVA-CYA 172/5 +AAZ23075.1|Q45R85 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces fradiae Unknown +AAZ23076.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces fradiae NRRL18158 +AAZ23077.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces fradiae NRRL18158 +AAZ23078.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces fradiae NRRL18158 +AAZ55898.1 Bacteria Bacillati Actinomycetota Actinomycetes Streptosporangiales Nocardiopsidaceae Thermobifida Thermobifida fusca YX +AAZ55899.1 Bacteria Bacillati Actinomycetota Actinomycetes Streptosporangiales Nocardiopsidaceae Thermobifida Thermobifida fusca YX +AAZ55900.1 Bacteria Bacillati Actinomycetota Actinomycetes Streptosporangiales Nocardiopsidaceae Thermobifida Thermobifida fusca YX +AAZ55904.1 Bacteria Bacillati Actinomycetota Actinomycetes Streptosporangiales Nocardiopsidaceae Thermobifida Thermobifida fusca YX +ABA23460.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Nostocaceae Trichormus Trichormus variabilis ATCC 29413 +ABA59547.1|Q1PSF4 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces tsusimaensis Unknown +ABA59548.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces tsusimaensis ATCC 15141 +ABA70582.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Penicillium Penicillium chrysogenum AS-P-78 +ABA73954.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas fluorescens Pf0-1 +ABA73955.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas fluorescens Pf0-1 +ABA73956.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas fluorescens Pf0-1 +ABB80392.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Lysobacterales Lysobacteraceae Lysobacter Lysobacter lactamgenus IFO14288 +ABC35522.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Burkholderiaceae Burkholderia Burkholderia thailandensis E264 E264; ATCC 700388 +ABC36203.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Burkholderiaceae Burkholderia Burkholderia thailandensis E264 E264; ATCC 700388 +ABC36785.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Burkholderiaceae Burkholderia Burkholderia thailandensis E264 E264; ATCC 700388 +ABC39418.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Burkholderiaceae Burkholderia Burkholderia thailandensis E264 E264; ATCC 700388 +ABD14711.1 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus cereus F4810/72 +ABD14712.1 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus cereus F4810/72 +ABD65956.1|Q06YZ3 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces fungicidicus Unknown +ABD65957.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces fungicidicus ATCC 21013 +ABD65958.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces fungicidicus ATCC 21013 +ABD65960.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces fungicidicus ATCC 21013 +ABF87031.1|YP_631961.1 Bacteria Pseudomonadati Pseudomonadota Deltaproteobacteria Myxococcales Myxococcaceae Myxococcus Myxococcus xanthus DK 1622 +ABG94125.1|YP_702283.1 Bacteria Bacillati Actinomycetota Actinomycetes Mycobacteriales Nocardiaceae Rhodococcus Rhodococcus jostii RHA1 +ABH06368.2 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas fluorescens SS101 +ABH06369.2 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas fluorescens SS101 +ABI22131.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces lavendulae NRRL 11002 +ABI22132.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces lavendulae NRRL 11002 +ABI22133.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces lavendulae NRRL 11002 +ABI26077.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Oscillatoriales Microcoleaceae Planktothrix Planktothrix agardhii NIVA-CYA 116 +ABI26078.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Oscillatoriales Microcoleaceae Planktothrix Planktothrix agardhii NIVA-CYA 116 +ABI26079.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Oscillatoriales Microcoleaceae Planktothrix Planktothrix agardhii NIVA-CYA 116 +ABL74936.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Streptoalloteichus Streptoalloteichus hindustanus ATCC 31158 +ABL74937.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Streptoalloteichus Streptoalloteichus hindustanus ATCC 31158 +ABL74939.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Streptoalloteichus Streptoalloteichus hindustanus ATCC 31158 +ABL74940.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Streptoalloteichus Streptoalloteichus hindustanus ATCC 31158 +ABL74945.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Streptoalloteichus Streptoalloteichus hindustanus ATCC 31158 +ABM21571.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Nostocaceae Nostoc Nostoc sp. ATCC 53789 +ABM21572.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Nostocaceae Nostoc Nostoc sp. ATCC 53789 +ABM91454.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Clavicipitaceae Epichloe Epichloe festucae var. lolii Lp19 +ABP55169.1 Bacteria Bacillati Actinomycetota Actinomycetes Micromonosporales Micromonosporaceae Salinispora Salinispora tropica CNB-440 +ABP57745.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Neisseriales Chromobacteriaceae Chromobacterium Chromobacterium violaceum 968 +ABP57748.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Neisseriales Chromobacteriaceae Chromobacterium Chromobacterium violaceum 968 +ABP57749.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Neisseriales Chromobacteriaceae Chromobacterium Chromobacterium violaceum 968 +ABP73646.1 Bacteria Bacillati Actinomycetota Actinomycetes Micromonosporales Micromonosporaceae Salinispora Salinispora tropica CNB-476 +ABQ96384.2 Bacteria Bacillati Bacillota Bacilli Bacillales Paenibacillaceae Paenibacillus Paenibacillus polymyxa PKB1 +ABR12615.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Penicillium Penicillium chrysogenum Wisconsin 54-1255 +ABR67744.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Saccharothrix Saccharothrix mutabilis subsp. capreolus Unknown +ABR67749.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Saccharothrix Saccharothrix mutabilis subsp. capreolus Unknown +ABR67750.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Saccharothrix Saccharothrix mutabilis subsp. capreolus Unknown +ABR67758.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Saccharothrix Saccharothrix mutabilis subsp. capreolus Unknown +ABS50184.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas fluorescens WCS374 +ABS74179.1|CAE11248.1 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus velezensis FZB42 +ABS74180.1 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus velezensis FZB42 +ABS74181.1|CAE11250.1 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus velezensis FZB42 +ABS74205.1 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus velezensis FZB42 +ABS74206.1 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus velezensis FZB42 +ABS74207.1 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus velezensis FZB42 +ABS74208.1 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus velezensis FZB42 +ABS74209.1|CAE11277.1 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus velezensis FZB42 +ABS75232.1 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus velezensis FZB42 +ABS75234.1 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus velezensis FZB42 +ABS87601.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus fumigatus Af293 Unknown +ABU70375.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Vibrionales Vibrionaceae Vibrio Vibrio campbellii ATCC BAA-1116 ATCC BAA-1116; BB120 +ABU70377.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Vibrionales Vibrionaceae Vibrio Vibrio campbellii ATCC BAA-1116 ATCC BAA-1116; BB120 +ABV56582.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Kutzneria Kutzneria sp. 744 +ABV56585.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Kutzneria Kutzneria sp. 744 +ABV56587.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Kutzneria Kutzneria sp. 744 +ABV56588.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Kutzneria Kutzneria sp. 744 +ABV56594.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Kutzneria Kutzneria sp. 744 +ABV79985.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Oscillatoriales Microcoleaceae Planktothrix Planktothrix agardhii NIVA-CYA 126/8 +ABV79986.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Oscillatoriales Microcoleaceae Planktothrix Planktothrix agardhii NIVA-CYA 126/8 +ABV79987.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Oscillatoriales Microcoleaceae Planktothrix Planktothrix agardhii NIVA-CYA 126/8 +ABV79988.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Oscillatoriales Microcoleaceae Planktothrix Planktothrix agardhii NIVA-CYA 126/8 +ABW00331.1 Bacteria Bacillati Actinomycetota Actinomycetes Micromonosporales Micromonosporaceae Salinispora Salinispora arenicola CNS-205 +ABW17375.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas putida PCL1445 +ABW17376.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas putida PCL1445 +ABW17377.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas putida PCL1445 +ABX37382.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Comamonadaceae Delftia Delftia acidovorans SPH-1 +ABX37383.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Comamonadaceae Delftia Delftia acidovorans SPH-1 +ABX37385.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Comamonadaceae Delftia Delftia acidovorans SPH-1 +ABX38811.1 Bacteria Bacillati Bacillota Bacilli Bacillales Paenibacillaceae Paenibacillus Paenibacillus polymyxa Unknown +ABX60161.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Aphanizomenonaceae Cylindrospermopsis Cylindrospermopsis raciborskii AWT205 +ACA97576.1 Bacteria Bacillati Bacillota Bacilli Bacillales Paenibacillaceae Paenibacillus Paenibacillus polymyxa Unknown +ACA97577.1 Bacteria Bacillati Bacillota Bacilli Bacillales Paenibacillaceae Paenibacillus Paenibacillus polymyxa Unknown +ACA97580.1 Bacteria Bacillati Bacillota Bacilli Bacillales Paenibacillaceae Paenibacillus Paenibacillus polymyxa Unknown +ACB12556.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Nectriaceae Fusarium Fusarium oxysporum FRC O-1890 +ACC81021.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Nostocaceae Nostoc Nostoc punctiforme PCC 73102 ATCC 29133; PCC 73102 +ACC81022.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Nostocaceae Nostoc Nostoc punctiforme PCC 73102 ATCC 29133; PCC 73102 +ACC81023.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Nostocaceae Nostoc Nostoc punctiforme PCC 73102 ATCC 29133; PCC 73102 +ACC81024.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Nostocaceae Nostoc Nostoc punctiforme PCC 73102 ATCC 29133; PCC 73102 +ACG60771.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces pilosus Unknown +ACG60772.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces pilosus Unknown +ACG60773.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces pilosus Unknown +ACG60776.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces pilosus Unknown +ACG60778.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces pilosus Unknown +ACG60782.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces pilosus Unknown +ACH90386.1 Eukaryota Fungi Basidiomycota Agaricomycetes Boletales Tapinellaceae Tapinella Tapinella panuoides Unknown +ACI30655.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Cordycipitaceae Beauveria Beauveria bassiana ATCC 7159 +ACJ04424.1 Eukaryota Fungi Ascomycota Dothideomycetes Dothideales Saccotheciaceae Aureobasidium Aureobasidium pullulans BP-1938 +ACM68684.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Chroococcales Microcystaceae Microcystis Microcystis aeruginosa NIES-98 +ACM68690.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Chroococcales Microcystaceae Microcystis Microcystis aeruginosa NIES-98 +ACN69986.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces antibioticus NRRL 8167 +ACO31297.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces platensis MA7327 +ACR33075.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Oscillatoriales Microcoleaceae Kamptonema Kamptonema sp. PCC 6506 +ACR78148.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Cordycipitaceae Beauveria Beauveria bassiana ATCC 7159 +ACS68554.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Clavicipitaceae Metarhizium Metarhizium anisopliae ARSEF 2575 +ACU36654.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Actinosynnema Actinosynnema mirum DSM 43827 +ACU36660.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Actinosynnema Actinosynnema mirum DSM 43827 +ACY06285.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces flaveolus DSM 9954 +ACZ55942.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Nostocaceae Anabaena Anabaena sp. 90 +ACZ55943.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Nostocaceae Anabaena Anabaena sp. 90 +ACZ55944.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Nostocaceae Anabaena Anabaena sp. 90 +ACZ55945.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Nostocaceae Anabaena Anabaena sp. 90 +ACZ55946.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Nostocaceae Anabaena Anabaena sp. 90 +ACZ66258.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Nectriaceae Fusarium Fusarium incarnatum Unknown +ADA69239.2 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Nostocaceae Nostoc Nostoc sp. 'Peltigera membranacea cyanobiont' Unknown +ADA82585.1 Bacteria None None None None None None uncultured bacterium psy1 Unknown +ADB02855.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Kibdelosporangium Kibdelosporangium sp. MJ126-NF4 +ADB02873.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Kibdelosporangium Kibdelosporangium sp. MJ126-NF4 +ADC79642.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. 307-9 +ADD82940.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas fluorescens BCCM_ID9359 +ADG27358.1|O68487|WP_057667184.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces anulatus Unknown +ADG27359.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces anulatus ATCC 11523 +ADH01485.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas sp. 2663 +ADH04641.1 Bacteria Pseudomonadati Myxococcota Polyangia Polyangiales Polyangiaceae Sorangium Sorangium cellulosum So ce895 +ADH04678.1 Bacteria Pseudomonadati Myxococcota Myxococcia Myxococcales Archangiaceae Cystobacter Cystobacter sp. SBCb004 +ADH04679.1 Bacteria Pseudomonadati Myxococcota Myxococcia Myxococcales Archangiaceae Cystobacter Cystobacter sp. SBCb004 +ADH04680.1 Bacteria Pseudomonadati Myxococcota Myxococcia Myxococcales Archangiaceae Cystobacter Cystobacter sp. SBCb004 +ADI24927.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Penicillium Penicillium aethiopicum IBT 5753 +ADI58643.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces nodosus subsp. asukaensis ATCC 29757 +ADJ63842.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Oxalobacteraceae Herbaspirillum Herbaspirillum seropedicae SmR1 +ADL64235.1 Bacteria Bacillati Bacillota Bacilli Bacillales Staphylococcaceae Staphylococcus Staphylococcus aureus subsp. aureus str. JKD6008 +ADM34138.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus sp. MF297-2 +ADN43685.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Cordycipitaceae Beauveria Beauveria bassiana 992.05 +ADQ55475.1 None None None None None None None uncultured organism Unknown +ADQ55476.1 None None None None None None None uncultured organism Unknown +ADQ74618.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas putida RW10S1 +ADY16689.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Penicillium Penicillium aethiopicum IBT 5753 +ADY16697.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Penicillium Penicillium aethiopicum IBT 5753 +ADY76664.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. DSM 5940 +ADY76667.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. DSM 5940 +ADY76674.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. DSM 5940 +ADY76684.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. DSM 5940 +ADZ24989.1 Bacteria Pseudomonadati Myxococcota Polyangia Polyangiales Polyangiaceae Sorangium Sorangium cellulosum So ce690 +ADZ24995.1 Bacteria Pseudomonadati Myxococcota Polyangia Polyangiales Polyangiaceae Sorangium Sorangium cellulosum So ce690 +ADZ24999.1 Bacteria Pseudomonadati Myxococcota Polyangia Polyangiales Polyangiaceae Sorangium Sorangium cellulosum So ce690 +AEA29643.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces albus subsp. albus ATCC 39897 +AEA29644.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces albus subsp. albus ATCC 39897 +AEA30272.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. Acta 2897 +AEA30273.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. Acta 2897 +AEA30274.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. Acta 2897 +AEA35021.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Nectriaceae Fusarium Fusarium fujikuroi 0825009 +AEA35027.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Nectriaceae Fusarium Fusarium fujikuroi 0825009 +AEC14346.1 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus sp. NK2003 +AEC14347.1 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus sp. NK2003 +AEC14348.1 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus sp. NK2003 +AEC14349.1 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus sp. NK2003 +AED90002.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas sp. SHC52 +AED90003.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas sp. SHC52 +AED90004.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas sp. SHC52 +AEE88284.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Coleofasciculales Coleofasciculaceae Moorena Moorena producens 3L +AEF33078.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces pyridomyceticus NRRL B-2517 +AEG64689.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces viridochromogenes ATCC 29814 +AEG64696.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces viridochromogenes ATCC 29814 +AEG64697.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces viridochromogenes ATCC 29814 +AEG64698.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces viridochromogenes ATCC 29814 +AEH41793.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces griseoflavus W-384 +AEH41794.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces griseoflavus W-384 +AEH42484.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces chartreusis NRRL 3882 +AEH59099.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Lysobacterales Lysobacteraceae Lysobacter Lysobacter sp. ATCC 53042 +AEH59100.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Lysobacterales Lysobacteraceae Lysobacter Lysobacter sp. ATCC 53042 +AEI58865.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Amycolatopsis Amycolatopsis orientalis HCCB10007 +AEI58866.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Amycolatopsis Amycolatopsis orientalis HCCB10007 +AEI58867.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Amycolatopsis Amycolatopsis orientalis HCCB10007 +AEI58879.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Amycolatopsis Amycolatopsis orientalis HCCB10007 +AEI70245.1 Bacteria Bacillati Bacillota Bacilli Bacillales Paenibacillaceae Paenibacillus Paenibacillus elgii B69 +AEO57481.1 Eukaryota Fungi Ascomycota Sordariomycetes Sordariales Chaetomiaceae Thermothelomyces Thermothelomyces thermophilus ATCC 42464 +AEP18655.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Lysobacterales Lysobacteraceae Lysobacter Lysobacter enzymogenes OH11 +AEP18656.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Lysobacterales Lysobacteraceae Lysobacter Lysobacter enzymogenes OH11 +AET13875.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Clavicipitaceae Epichloe Epichloe festucae E2368 +AET13879.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Clavicipitaceae Epichloe Epichloe festucae F11 +AET79179.1|CCE30235.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Clavicipitaceae Claviceps Claviceps purpurea 20.1 +AET79183.1|CCE30226.1|sp_M1W0X8.1_LPSA1_CLAP2 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Clavicipitaceae Claviceps Claviceps purpurea 20.1 +AET79184.1|CCE30225.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Clavicipitaceae Claviceps Claviceps purpurea 20.1 +AET98905.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces griseovariabilis subsp. bandungensis 2507 +AET98906.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces griseovariabilis subsp. bandungensis 2507 +AET98914.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces griseovariabilis subsp. bandungensis 2507 +AET98916.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces griseovariabilis subsp. bandungensis 2507 +AEU11003.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Nodulariaceae Kaarinaea Kaarinaea lacus PCC 9237 152 +AEU11006.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Nodulariaceae Kaarinaea Kaarinaea lacus PCC 9237 152 +AEV21218.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Clavicipitaceae Periglandula Periglandula ipomoeae lasaF13 +AEV21228.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Clavicipitaceae Periglandula Periglandula ipomoeae lasaF13 +AEV21230.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Clavicipitaceae Periglandula Periglandula ipomoeae lasaF13 +AEZ51516.1 Bacteria Bacillati Bacillota Bacilli Bacillales Paenibacillaceae Paenibacillus Paenibacillus polymyxa PKB1 +AEZ51517.1 Bacteria Bacillati Bacillota Bacilli Bacillales Paenibacillaceae Paenibacillus Paenibacillus polymyxa PKB1 +AEZ51520.1 Bacteria Bacillati Bacillota Bacilli Bacillales Paenibacillaceae Paenibacillus Paenibacillus polymyxa PKB1 +AFA26384.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus flavus CA28 +AFB76152.1 Eukaryota Fungi Basidiomycota Agaricomycetes Boletales Suillaceae Suillus Suillus grevillei Unknown +AFH75320.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas sessilinigenes CMR12a +AFH75321.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas sessilinigenes CMR12a +AFH75322.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas sessilinigenes CMR12a +AFH75328.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas sessilinigenes CMR12a +AFH75329.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas sessilinigenes CMR12a +AFH75330.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas sessilinigenes CMR12a +AFJ14793.1 Bacteria Bacillati Bacillota Bacilli Bacillales Paenibacillaceae Paenibacillus Paenibacillus elgii B69 +AFJ14794.1 Bacteria Bacillati Bacillota Bacilli Bacillales Paenibacillaceae Paenibacillus Paenibacillus elgii B69 +AFJ14795.1 Bacteria Bacillati Bacillota Bacilli Bacillales Paenibacillaceae Paenibacillus Paenibacillus elgii B69 +AFJ20782.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. ATCC 700974 +AFJ23819.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas putida RW10S2 +AFJ23825.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas putida RW10S2 +AFJ23826.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas putida RW10S2 +AFK57212.1 Bacteria Pseudomonadati Pseudomonadota Alphaproteobacteria Geminicoccales Geminicoccaceae Tistrella Tistrella mobilis KA081020-065 +AFK57214.1 Bacteria Pseudomonadati Pseudomonadota Alphaproteobacteria Geminicoccales Geminicoccaceae Tistrella Tistrella mobilis KA081020-065 +AFK57215.1 Bacteria Pseudomonadati Pseudomonadota Alphaproteobacteria Geminicoccales Geminicoccaceae Tistrella Tistrella mobilis KA081020-065 +AFK57219.1 Bacteria Pseudomonadati Pseudomonadota Alphaproteobacteria Geminicoccales Geminicoccaceae Tistrella Tistrella mobilis KA081020-065 +AFK57220.1 Bacteria Pseudomonadati Pseudomonadota Alphaproteobacteria Geminicoccales Geminicoccaceae Tistrella Tistrella mobilis KA081020-065 +AFK57221.1 Bacteria Pseudomonadati Pseudomonadota Alphaproteobacteria Geminicoccales Geminicoccaceae Tistrella Tistrella mobilis KA081020-065 +AFN69082.1 Eukaryota Fungi Ascomycota Dothideomycetes Pleosporales Pleosporaceae Alternaria Alternaria alternata EV-MIL31 +AFO85453.1 Bacteria Bacillati Actinomycetota Actinomycetes Streptosporangiales Nocardiopsidaceae Marinactinospora Marinactinospora thermotolerans SCSIO 00652 +AFP73394.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Nectriaceae Fusarium Fusarium fujikuroi IMI 58289 +AFP87549.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Morganellaceae Xenorhabdus Xenorhabdus budapestensis Unknown +AFR69334.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas sp. Q71576 +AFT91378.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus rugulosus NRRL 11440 +AFV52191.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Streptoalloteichus Streptoalloteichus sp. ATCC 53650 +AFZ61501.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas fluorescens LMG 5329 +AFZ61525.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas fluorescens LMG 5329 +AFZ61526.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas fluorescens LMG 5329 +AGA37267.1 Eukaryota Fungi Ascomycota Eurotiomycetes Onygenales Malbrancheaceae Malbranchea Malbranchea aurantiaca RRC1813 +AGA37269.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Penicillium Penicillium fellutanum ATCC 20841 +AGC24265.1 Bacteria Bacillati Actinomycetota Actinomycetes Streptosporangiales Streptosporangiaceae Nonomuraea Nonomuraea spiralis IMC A-0156 +AGC45618.1 Bacteria Pseudomonadati Myxococcota Myxococcia Myxococcales Myxococcaceae Myxococcus Myxococcus stipitatus DSM 14675 +AGC65513.1 Bacteria Pseudomonadati Pseudomonadota Alphaproteobacteria Rhodospirillales Thalassospiraceae Thalassospira Thalassospira sp. CNJ-328 +AGC65514.1 Bacteria Pseudomonadati Pseudomonadota Alphaproteobacteria Rhodospirillales Thalassospiraceae Thalassospira Thalassospira sp. CNJ-328 +AGC65515.1 Bacteria Pseudomonadati Pseudomonadota Alphaproteobacteria Rhodospirillales Thalassospiraceae Thalassospira Thalassospira sp. CNJ-328 +AGC65516.1 Bacteria Pseudomonadati Pseudomonadota Alphaproteobacteria Geminicoccales Geminicoccaceae Tistrella Tistrella bauzanensis TIO7329 +AGC65517.1 Bacteria Pseudomonadati Pseudomonadota Alphaproteobacteria Geminicoccales Geminicoccaceae Tistrella Tistrella bauzanensis TIO7329 +AGC83576.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus versicolor NRRL35600 +AGD80616.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces lusitanus NRRL8034 +AGD80623.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces lusitanus NRRL8034 +AGE11891.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. NRRL F-4415 +AGE11892.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. NRRL F-4415 +AGE11898.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. NRRL F-4415 +AGE11899.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. NRRL F-4415 +AGE25479.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas poae RE*1-1-14 +AGE25480.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas poae RE*1-1-14 +AGE26255.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas poae RE*1-1-14 +AGM14925.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas putida BW11M1 +AGM14933.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas putida BW11M1 +AGM14934.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas putida BW11M1 +AGM16412.1 Bacteria Bacillati Bacillota Bacilli Bacillales Paenibacillaceae Paenibacillus Paenibacillus sp. OSY-SE +AGM16413.1 Bacteria Bacillati Bacillota Bacilli Bacillales Paenibacillaceae Paenibacillus Paenibacillus sp. OSY-SE +AGM16414.1 Bacteria Bacillati Bacillota Bacilli Bacillales Paenibacillaceae Paenibacillus Paenibacillus sp. OSY-SE +AGN11881.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Burkholderiaceae Burkholderia Burkholderia humptydooensis MSMB43 +AGN74876.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces griseoviridis Unknown +AGN74880.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces griseoviridis Unknown +AGN74885.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces griseoviridis Unknown +AGN74886.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces griseoviridis Unknown +AGN74892.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces griseoviridis Unknown +AGN74895.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces griseoviridis Unknown +AGN74898.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces griseoviridis Unknown +AGO86662.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Nectriaceae Fusarium Fusarium heterosporum ATCC 74349 +AGQ43600.1 Eukaryota Fungi Ascomycota Dothideomycetes Pleosporales Pleosporaceae Alternaria Alternaria jesenskae Unknown +AGS06887.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria None None Profftella Profftella armatura DC +AGS77307.1 Bacteria Bacillati Actinomycetota Actinomycetes Micromonosporales Micromonosporaceae Actinoplanes Actinoplanes sp. ATCC 53533 +AGS77308.1 Bacteria Bacillati Actinomycetota Actinomycetes Micromonosporales Micromonosporaceae Actinoplanes Actinoplanes sp. ATCC 53533 +AGS77309.1 Bacteria Bacillati Actinomycetota Actinomycetes Micromonosporales Micromonosporaceae Actinoplanes Actinoplanes sp. ATCC 53533 +AGS77310.1 Bacteria Bacillati Actinomycetota Actinomycetes Micromonosporales Micromonosporaceae Actinoplanes Actinoplanes sp. ATCC 53533 +AGY30674.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces calvus ATCC 13382 +AGY30675.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces calvus ATCC 13382 +AGZ03650.1 Bacteria Bacillati Bacillota Bacilli Bacillales Paenibacillaceae Paenibacillus Paenibacillus larvae DSM 25430 +AGZ03651.1 Bacteria Bacillati Bacillota Bacilli Bacillales Paenibacillaceae Paenibacillus Paenibacillus larvae DSM 25430 +AGZ15455.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. MK498-98F14 +AGZ15458.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. MK498-98F14 +AGZ15459.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. MK498-98F14 +AGZ15460.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. MK498-98F14 +AGZ15476.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. MK498-98F14 +AHB38497.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Goodfellowiella Goodfellowiella coeruleoviolacea ATCC 53904 +AHB38511.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces hygroscopicus ATCC 53709 +AHB38515.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces hygroscopicus ATCC 53709 +AHB82056.1 Bacteria Pseudomonadati Myxococcota Polyangia Polyangiales Polyangiaceae Sorangium Sorangium cellulosum So ce38 +AHB82058.1 Bacteria Pseudomonadati Myxococcota Polyangia Polyangiales Polyangiaceae Sorangium Sorangium cellulosum So ce38 +AHB82059.1 Bacteria Pseudomonadati Myxococcota Polyangia Polyangiales Polyangiaceae Sorangium Sorangium cellulosum So ce38 +AHB82069.1 Bacteria Pseudomonadati Myxococcota Polyangia Polyangiales Polyangiaceae Jahnella Jahnella sp. MSr9139 +AHB82071.1 Bacteria Pseudomonadati Myxococcota Polyangia Polyangiales Polyangiaceae Jahnella Jahnella sp. MSr9139 +AHB82072.1 Bacteria Pseudomonadati Myxococcota Polyangia Polyangiales Polyangiaceae Jahnella Jahnella sp. MSr9139 +AHD05614.1 Bacteria Bacillati Bacillota Bacilli Bacillales Paenibacillaceae Paenibacillus Paenibacillus larvae subsp. larvae DSM 25430 +AHD05615.1 Bacteria Bacillati Bacillota Bacilli Bacillales Paenibacillaceae Paenibacillus Paenibacillus larvae subsp. larvae DSM 25430 +AHD05616.1 Bacteria Bacillati Bacillota Bacilli Bacillales Paenibacillaceae Paenibacillus Paenibacillus larvae subsp. larvae DSM 25430 +AHD05617.1 Bacteria Bacillati Bacillota Bacilli Bacillales Paenibacillaceae Paenibacillus Paenibacillus larvae subsp. larvae DSM 25430 +AHD05618.1 Bacteria Bacillati Bacillota Bacilli Bacillales Paenibacillaceae Paenibacillus Paenibacillus larvae subsp. larvae DSM 25430 +AHD05621.1 Bacteria Bacillati Bacillota Bacilli Bacillales Paenibacillaceae Paenibacillus Paenibacillus larvae subsp. larvae DSM 25430 +AHD05627.1 Bacteria Bacillati Bacillota Bacilli Bacillales Paenibacillaceae Paenibacillus Paenibacillus larvae subsp. larvae DSM 25430 +AHD05677.1 Bacteria Bacillati Bacillota Bacilli Bacillales Paenibacillaceae Paenibacillus Paenibacillus larvae subsp. larvae DSM 25430 +AHD05678.1 Bacteria Bacillati Bacillota Bacilli Bacillales Paenibacillaceae Paenibacillus Paenibacillus larvae subsp. larvae DSM 25430 +AHD05679.1 Bacteria Bacillati Bacillota Bacilli Bacillales Paenibacillaceae Paenibacillus Paenibacillus larvae subsp. larvae DSM 25430 +AHF20582.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Amycolatopsis Amycolatopsis sp. MJM2582 +AHF20583.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Amycolatopsis Amycolatopsis sp. MJM2582 +AHF20584.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Amycolatopsis Amycolatopsis sp. MJM2582 +AHF20585.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Amycolatopsis Amycolatopsis sp. MJM2582 +AHF21228.1 Bacteria Bacillati Bacillota Bacilli Bacillales Paenibacillaceae Paenibacillus Paenibacillus terrae NRRL B-30644 +AHF21229.1 Bacteria Bacillati Bacillota Bacilli Bacillales Paenibacillaceae Paenibacillus Paenibacillus terrae NRRL B-30644 +AHH53506.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Saccharomonospora Saccharomonospora piscinae CNQ490 +AHH53507.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Saccharomonospora Saccharomonospora piscinae CNQ490 +AHH53508.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Saccharomonospora Saccharomonospora piscinae CNQ490 +AHI59108.1 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus subtilis 916 +AHI59109.1 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus subtilis 916 +AHI59110.1 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus subtilis 916 +AHJ31215.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Nodulariaceae Nodularia Nodularia spumigena CCY9414 +AHN91924.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. LZ35 +AHY86403.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas corrugata CFBP 5454 +AHZ20766.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Nostocaceae Anabaena Anabaena sp. Syke748 Unknown +AHZ20773.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Nostocaceae Anabaena Anabaena sp. Syke748 Unknown +AHZ20774.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Nostocaceae Anabaena Anabaena sp. Syke748 Unknown +AHZ20781.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Nostocaceae Anabaena Anabaena sp. Syke748 Unknown +AHZ20784.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Nostocaceae Anabaena Anabaena sp. Syke748 Unknown +AHZ34232.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas cichorii SF1-54 +AHZ34233.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas cichorii SF1-54 +AHZ34238.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas cichorii SF1-54 +AHZ34239.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas cichorii SF1-54 +AHZ34240.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas cichorii SF1-54 +AHZ34241.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas cichorii SF1-54 +AHZ34242.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas cichorii SF1-54 +AHZ34243.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas cichorii SF1-54 +AIC32693.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Burkholderiaceae Burkholderia Burkholderia sp. FERM BP-3421 +AID65222.1 Bacteria Pseudomonadati Myxococcota Myxococcia Myxococcales Archangiaceae Cystobacter Cystobacter fuscus MCy9118 +AID65224.1 Bacteria Pseudomonadati Myxococcota Myxococcia Myxococcales Archangiaceae Cystobacter Cystobacter fuscus MCy9118 +AID65225.1 Bacteria Pseudomonadati Myxococcota Myxococcia Myxococcales Archangiaceae Cystobacter Cystobacter fuscus MCy9118 +AIE77057.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Amycolatopsis Amycolatopsis lurida NRRL2430 +AIE77058.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Amycolatopsis Amycolatopsis lurida NRRL2430 +AIE77059.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Amycolatopsis Amycolatopsis lurida NRRL2430 +AIE77060.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Amycolatopsis Amycolatopsis lurida NRRL2430 +AIE77076.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Amycolatopsis Amycolatopsis lurida NRRL2430 +AIG79224.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Amycolatopsis Amycolatopsis japonica MG417-CF17 +AIG79240.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Amycolatopsis Amycolatopsis japonica MG417-CF17 +AIG79241.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Amycolatopsis Amycolatopsis japonica MG417-CF17 +AIG79242.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Amycolatopsis Amycolatopsis japonica MG417-CF17 +AIG79243.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Amycolatopsis Amycolatopsis japonica MG417-CF17 +AIP87510.1 Eukaryota Fungi None None None None None fungal sp. NRRL 50135 +AIR74925.1|CBD77749.1 Bacteria Pseudomonadati Myxococcota Polyangia Polyangiales Polyangiaceae Chondromyces Chondromyces crocatus Cm c5 +AIR74926.1|CBD77746.1 Bacteria Pseudomonadati Myxococcota Polyangia Polyangiales Polyangiaceae Chondromyces Chondromyces crocatus Cm c5 +AIS24862.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces netropsis Unknown +AIT38302.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces toxytricini NRRL 15443 +AIW58892.1 Bacteria Bacillati Actinomycetota Actinomycetes Streptosporangiales Streptosporangiaceae Nonomuraea Nonomuraea sp. MJM5123 +AIW82277.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Nostocaceae Cylindrospermum Cylindrospermum alatosporum CCALA 988 +AIW82282.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Nostocaceae Cylindrospermum Cylindrospermum alatosporum CCALA 988 +AIW82283.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Nostocaceae Cylindrospermum Cylindrospermum alatosporum CCALA 988 +AIW82284.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Nostocaceae Cylindrospermum Cylindrospermum alatosporum CCALA 988 +AIW82285.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Nostocaceae Cylindrospermum Cylindrospermum alatosporum CCALA 988 +AJF34463.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales None Eleftheria Eleftheria terrae ISO18629 +AJF34464.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales None Eleftheria Eleftheria terrae ISO18629 +AJM89734.1 Bacteria Bacillati Bacillota Bacilli Bacillales Paenibacillaceae Paenibacillus Paenibacillus alvei LR +AJM89735.1 Bacteria Bacillati Bacillota Bacilli Bacillales Paenibacillaceae Paenibacillus Paenibacillus alvei LR +AJM89738.1 Bacteria Bacillati Bacillota Bacilli Bacillales Paenibacillaceae Paenibacillus Paenibacillus alvei LR +AJV88375.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces drozdowiczii SCSIO 10141 +AJV88376.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces drozdowiczii SCSIO 10141 +AJV88377.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces drozdowiczii SCSIO 10141 +AJV88383.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces drozdowiczii SCSIO 10141 +AJW76709.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces scopuliridis SCSIO ZJ46 +AJW76710.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces scopuliridis SCSIO ZJ46 +AJW76711.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces scopuliridis SCSIO ZJ46 +AJY78094.1 Bacteria Pseudomonadati Myxococcota Myxococcia Myxococcales Myxococcaceae Myxococcus Myxococcus virescens ST200611 +AKA59436.1 Bacteria None None None None None None uncultured bacterium AR_412 Unknown +AKA59447.1 Bacteria None None None None None None uncultured bacterium AR_456 Unknown +AKC54422.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Cordycipitaceae Cordyceps Cordyceps fumosorosea ARSEF 2679 +AKC91849.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces muensis DSM 40835 +AKC91856.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces muensis DSM 40835 +AKC91857.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces muensis DSM 40835 +AKJ70942.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus mulundensis Y-30462 +AKL78825.1 Eukaryota Fungi Ascomycota Leotiomycetes Helotiales Helotiaceae Glarea Glarea lozoyensis ATCC 20868 +AKP45395.1 Bacteria Pseudomonadati Myxococcota Myxococcia Myxococcales Archangiaceae Cystobacter Cystobacter sp. Cbv34 +AKP45396.1 Bacteria Pseudomonadati Myxococcota Myxococcia Myxococcales Archangiaceae Cystobacter Cystobacter sp. Cbv34 +AKP45399.1 Bacteria Pseudomonadati Pseudomonadota Deltaproteobacteria Myxococcales Archangiaceae Cystobacter Cystobacter sp. Cbv34 +AKP45400.1 Bacteria Pseudomonadati Myxococcota Myxococcia Myxococcales Archangiaceae Cystobacter Cystobacter sp. Cbv34 +ALG65313.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces calvus ATCC 13382 +ALG65314.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces calvus ATCC 13382 +ALG65317.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces calvus ATCC 13382 +ALG65318.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces calvus ATCC 13382 +ALG65319.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces calvus ATCC 13382 +ALK27914.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. DSM 11171 +ALK27915.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. DSM 11171 +ALK27916.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. DSM 11171 +ALO65125.1 Eukaryota Fungi Basidiomycota Agaricomycetes Polyporales Gelatoporiaceae Gelatoporia Gelatoporia subvermispora B +ALO65126.1 Eukaryota Fungi Basidiomycota Agaricomycetes Polyporales Gelatoporiaceae Gelatoporia Gelatoporia subvermispora B +ALU98443.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces globisporus C-1027 +ALV82356.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces rochei Sal35 +ALV82384.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces rochei Sal35 +ALV82388.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces rochei Sal35 +ALV86866.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces canus ATCC 12647 +ALV86867.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces canus ATCC 12647 +ALV86868.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces canus ATCC 12647 +AMM63162.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus nidulans NRRL 8112 Unknown +AMM63166.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus nidulans NRRL 8112 Unknown +AMQ36132.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Penicillium Penicillium sp. YT-2016 Unknown +AMQ36134.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Penicillium Penicillium sp. YT-2016 Unknown +AMT84997.1 Eukaryota Fungi Ascomycota Dothideomycetes Pleosporales Pleosporaceae Alternaria Alternaria alternata ZJ33 +AND66115.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus terreus SBUG844 +ANH11404.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. SD85 +ANH11405.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. SD85 +ANH22643.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Clavicipitaceae Metarhizium Metarhizium robertsii Unknown +ANI24100.1 Bacteria Pseudomonadati Myxococcota Polyangia Polyangiales Polyangiaceae Polyangium Polyangium spumosum Pl sm9 +ANQ43347.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas synxantha CR32 +ANQ43348.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas synxantha CR32 +ANQ43349.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas synxantha CR32 +ANX99773.1 Eukaryota Fungi Basidiomycota Agaricomycetes Russulales Bondarzewiaceae Heterobasidion Heterobasidion annosum Unknown +ANX99774.1 Eukaryota Fungi Basidiomycota Agaricomycetes Boletales Serpulaceae Serpula Serpula lacrymans Unknown +ANX99775.1 Eukaryota Fungi Basidiomycota Agaricomycetes Boletales Serpulaceae Serpula Serpula lacrymans Unknown +ANX99776.1 Eukaryota Fungi Basidiomycota Agaricomycetes Agaricales Psathyrellaceae Coprinopsis Coprinopsis cinerea Unknown +ANX99777.1 Eukaryota Fungi Basidiomycota Agaricomycetes Agaricales Psathyrellaceae Coprinopsis Coprinopsis cinerea Unknown +ANY57892.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Penicillium Penicillium thymicola Unknown +ANZ15839.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces noursei ATCC 11455 +ANZ15840.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces noursei ATCC 11455 +AOA33121.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas fluorescens BW11P2 +AOA33122.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas fluorescens BW11P2 +AOA33123.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas fluorescens BW11P2 +AOZ21316.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Burkholderiaceae Paraburkholderia Paraburkholderia acidicola ATCC 31363 +AOZ21320.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Burkholderiaceae Paraburkholderia Paraburkholderia acidicola ATCC 31363 +APD26279.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces pactum SCSIO 02999 +APU91750.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas tolaasii KACC10082 +APU91751.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas tolaasii KACC10082 +APZ78679.1 Bacteria Pseudomonadati Myxococcota Myxococcia Myxococcales None None Cystobacterineae bacterium CcG34 +APZ78680.1 Bacteria Pseudomonadati Myxococcota Myxococcia Myxococcales None None Cystobacterineae bacterium CcG34 +APZ78691.1 Bacteria Pseudomonadati Myxococcota Myxococcia Myxococcales Archangiaceae Hyalangium Hyalangium minutum DSM 14724 +APZ78692.1 Bacteria Pseudomonadati Myxococcota Myxococcia Myxococcales Archangiaceae Hyalangium Hyalangium minutum DSM 14724 +APZ78703.1 Bacteria Pseudomonadati Myxococcota Myxococcia Myxococcales Archangiaceae Hyalangium Hyalangium minutum Hym-3 +APZ78704.1 Bacteria Pseudomonadati Myxococcota Myxococcia Myxococcales Archangiaceae Hyalangium Hyalangium minutum Hym-3 +APZ78715.1 Bacteria Pseudomonadati Myxococcota Myxococcia Myxococcales Archangiaceae Hyalangium Hyalangium minutum NOCb10 +APZ78716.1 Bacteria Pseudomonadati Myxococcota Myxococcia Myxococcales Archangiaceae Hyalangium Hyalangium minutum NOCb10 +APZ78728.1 Bacteria Pseudomonadati Myxococcota Myxococcia Myxococcales Myxococcaceae Myxococcus Myxococcus sp. 171 +APZ78729.1 Bacteria Pseudomonadati Myxococcota Myxococcia Myxococcales Myxococcaceae Myxococcus Myxococcus sp. 171 +APZ78743.1 Bacteria Pseudomonadati Myxococcota Myxococcia Myxococcales Myxococcaceae Myxococcus Myxococcus fulvus HW-1 +APZ78744.1 Bacteria Pseudomonadati Myxococcota Myxococcia Myxococcales Myxococcaceae Myxococcus Myxococcus fulvus HW-1 +APZ78755.1 Bacteria Pseudomonadati Myxococcota Myxococcia Myxococcales Myxococcaceae Pseudomyxococcus Pseudomyxococcus hansupus mixupus +APZ78756.1 Bacteria Pseudomonadati Myxococcota Myxococcia Myxococcales Myxococcaceae Pseudomyxococcus Pseudomyxococcus hansupus mixupus +APZ78768.1 Bacteria Pseudomonadati Myxococcota Myxococcia Myxococcales Myxococcaceae Myxococcus Myxococcus xanthus DK 1622 +APZ78769.1 Bacteria Pseudomonadati Myxococcota Myxococcia Myxococcales Myxococcaceae Myxococcus Myxococcus xanthus DK 1622 +APZ78781.1 Bacteria Pseudomonadati Myxococcota Myxococcia Myxococcales Myxococcaceae Myxococcus Myxococcus xanthus DK897 +APZ78782.1 Bacteria Pseudomonadati Myxococcota Myxococcia Myxococcales Myxococcaceae Myxococcus Myxococcus xanthus DK897 +APZ78794.1 Bacteria Pseudomonadati Myxococcota Myxococcia Myxococcales Myxococcaceae Myxococcus Myxococcus xanthus A47 +APZ78795.1 Bacteria Pseudomonadati Myxococcota Myxococcia Myxococcales Myxococcaceae Myxococcus Myxococcus xanthus A47 +APZ78808.1 Bacteria Pseudomonadati Myxococcota Myxococcia Myxococcales Myxococcaceae Myxococcus Myxococcus xanthus Mx48 +APZ78809.1 Bacteria Pseudomonadati Myxococcota Myxococcia Myxococcales Myxococcaceae Myxococcus Myxococcus xanthus Mx48 +APZ78821.1|CAG29031.1|Q50JA3 Bacteria Pseudomonadati Pseudomonadota Deltaproteobacteria Myxococcales Archangiaceae Stigmatella Stigmatella aurantiaca Unknown +APZ78822.1|CAG29032.1 Bacteria Pseudomonadati Myxococcota Myxococcia Myxococcales Archangiaceae Stigmatella Stigmatella aurantiaca Unknown +APZ78833.1 Bacteria Pseudomonadati Myxococcota Myxococcia Myxococcales Archangiaceae Stigmatella Stigmatella aurantiaca Sg a15 +APZ78834.1 Bacteria Pseudomonadati Myxococcota Myxococcia Myxococcales Archangiaceae Stigmatella Stigmatella aurantiaca Sg a15 +APZ78845.1 Bacteria Pseudomonadati Myxococcota Myxococcia Myxococcales Archangiaceae Stigmatella Stigmatella aurantiaca Sg a32 +APZ78846.1 Bacteria Pseudomonadati Myxococcota Myxococcia Myxococcales Archangiaceae Stigmatella Stigmatella aurantiaca Sg a32 +APZ78855.1 Bacteria Pseudomonadati Myxococcota Myxococcia Myxococcales Archangiaceae Stigmatella Stigmatella erecta Pde77 +APZ78856.1 Bacteria Pseudomonadati Myxococcota Myxococcia Myxococcales Archangiaceae Stigmatella Stigmatella erecta Pde77 +AQH32481.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Hapalosiphonaceae Fischerella Fischerella sp. CENA161 +AQH32484.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Hapalosiphonaceae Fischerella Fischerella sp. CENA161 +AQH32485.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Hapalosiphonaceae Fischerella Fischerella sp. CENA161 +AQH32486.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Hapalosiphonaceae Fischerella Fischerella sp. CENA161 +AQM37583.1 Bacteria Pseudomonadati Myxococcota Myxococcia Myxococcales Myxococcaceae Myxococcus Myxococcus virescens ST200611 +AQM37584.1 Bacteria Pseudomonadati Myxococcota Myxococcia Myxococcales Myxococcaceae Myxococcus Myxococcus virescens ST200611 +AQM58286.1 None None None None None None None Shuttle vector AtFAC9J20 Unknown +AQV04224.1 Eukaryota Fungi Ascomycota Eurotiomycetes Chaetothyriales Chaetothyriaceae None Chaetothyriaceae sp. Unknown +AQV04230.1 Eukaryota Fungi Ascomycota Dothideomycetes Pleosporales Pleosporaceae Alternaria Alternaria oxytropis Unknown +AQX36215.1|sp_A0A248AFK6.1_NPS2_CERS8 Eukaryota Fungi Basidiomycota Agaricomycetes Polyporales Gelatoporiaceae Gelatoporia Gelatoporia subvermispora B +AQZ26587.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas fluorescens ATCC 39502 +AQZ42163.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales None Gliocladium Gliocladium sp. XZC04-CC-302 +AQZ69227.1 Bacteria Bacillati Actinomycetota Actinomycetes Streptosporangiales Streptosporangiaceae Nonomuraea Nonomuraea parvosata subsp. kistnae ATCC 55076 +AQZ69228.1 Bacteria Bacillati Actinomycetota Actinomycetes Streptosporangiales Streptosporangiaceae Nonomuraea Nonomuraea parvosata subsp. kistnae ATCC 55076 +AQZ69229.1 Bacteria Bacillati Actinomycetota Actinomycetes Streptosporangiales Streptosporangiaceae Nonomuraea Nonomuraea parvosata subsp. kistnae ATCC 55076 +AQZ71347.1 Bacteria Bacillati Actinomycetota Actinomycetes Streptosporangiales Streptosporangiaceae Nonomuraea Nonomuraea parvosata subsp. kistnae ATCC 55076 +ARB50206.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Clavicipitaceae Claviceps Claviceps africana Cla9 +ARB50207.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Clavicipitaceae Claviceps Claviceps africana Cla9 +ARO38317.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Coleofasciculales Coleofasciculaceae Moorena Moorena producens JHB +ARP51711.1 Eukaryota Fungi Ascomycota Dothideomycetes Botryosphaeriales Phyllostictaceae Phyllosticta Phyllosticta cirsii Unknown +ARR97036.1 Bacteria Bacillati Chloroflexota Chloroflexia Herpetosiphonales Herpetosiphonaceae Herpetosiphon Herpetosiphon sp. B060 +ARR97038.1 Bacteria Bacillati Chloroflexota Chloroflexia Herpetosiphonales Herpetosiphonaceae Herpetosiphon Herpetosiphon sp. B060 +ARR97039.1 Bacteria Bacillati Chloroflexota Chloroflexia Herpetosiphonales Herpetosiphonaceae Herpetosiphon Herpetosiphon sp. B060 +ARU08063.1 Bacteria None None None None None None uncultured bacterium Unknown +ARU08073.1 Bacteria None None None None None None uncultured bacterium Unknown +ARU08074.1 Bacteria None None None None None None uncultured bacterium Unknown +ARU08075.1 Bacteria None None None None None None uncultured bacterium Unknown +ASX95241.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces atratus SCSIO ZH16 +ATD05719.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Alteromonadales Pseudoalteromonadaceae Pseudoalteromonas Pseudoalteromonas piscicida JCM 20779 +ATD05720.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Alteromonadales Pseudoalteromonadaceae Pseudoalteromonas Pseudoalteromonas piscicida JCM 20779 +ATD51279.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Lysobacterales Lysobacteraceae Lysobacter Lysobacter enzymogenes OH11 +ATD51280.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Lysobacterales Lysobacteraceae Lysobacter Lysobacter enzymogenes OH11 +ATG32071.1 Bacteria Pseudomonadati Myxococcota Polyangia Nannocystales Nannocystaceae Nannocystis Nannocystis pusilla Ari7 +ATG32076.1 Bacteria Pseudomonadati Myxococcota Polyangia Nannocystales Nannocystaceae Nannocystis Nannocystis pusilla Ari7 +ATJ34002.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. ATCC 14903 +ATJ34005.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. ATCC 14903 +ATL73036.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces pactum SCSIO 02999 +ATL73045.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces pactum SCSIO 02999 +ATO51563.1 Bacteria Bacillati Bacillota Bacilli Bacillales Paenibacillaceae Brevibacillus Brevibacillus laterosporus DSM 25 +ATP76239.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Nostocaceae Nostoc Nostoc sp. CENA543 +ATP76243.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Nostocaceae Nostoc Nostoc sp. CENA543 +ATP76244.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Nostocaceae Nostoc Nostoc sp. CENA543 +ATP76246.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Nostocaceae Nostoc Nostoc sp. CENA543 +ATQ39428.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Bionectriaceae Amphichorda Amphichorda felina TTI-0347 +ATU31794.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. KCB13F003 +ATU31795.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. KCB13F003 +ATV95610.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Amycolatopsis Amycolatopsis sp. Hca4 +ATV95617.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Amycolatopsis Amycolatopsis sp. Hca4 +ATY37588.1 Bacteria Bacillati Bacillota Bacilli Bacillales Paenibacillaceae Brevibacillus Brevibacillus laterosporus DSM 25 +ATY37589.1 Bacteria Bacillati Bacillota Bacilli Bacillales Paenibacillaceae Brevibacillus Brevibacillus laterosporus DSM 25 +ATY37590.1 Bacteria Bacillati Bacillota Bacilli Bacillales Paenibacillaceae Brevibacillus Brevibacillus laterosporus DSM 25 +ATY37591.1 Bacteria Bacillati Bacillota Bacilli Bacillales Paenibacillaceae Brevibacillus Brevibacillus laterosporus DSM 25 +ATY37592.1 Bacteria Bacillati Bacillota Bacilli Bacillales Paenibacillaceae Brevibacillus Brevibacillus laterosporus DSM 25 +ATY37596.1 Bacteria Bacillati Bacillota Bacilli Bacillales Paenibacillaceae Brevibacillus Brevibacillus laterosporus DSM 25 +ATY37608.1 Bacteria Bacillati Bacillota Bacilli Bacillales Paenibacillaceae Brevibacillus Brevibacillus laterosporus DSM 25 +ATY37609.1 Bacteria Bacillati Bacillota Bacilli Bacillales Paenibacillaceae Brevibacillus Brevibacillus laterosporus DSM 25 +ATY61556.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Cordycipitaceae Cordyceps Cordyceps militaris ATCC 34164 +ATY69551.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. CB01883 Unknown +ATY69568.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. CB01883 Unknown +ATY69584.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. CB02120-2 Unknown +ATY69590.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. CB02120-2 Unknown +AUO29225.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus terreus FGSC A1156 +AUO29226.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus terreus FGSC A1156 +AUS29484.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus carbonarius Unknown +AUS29489.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus niger Unknown +AUS29494.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Penicillium Penicillium nordicum Unknown +AUS29499.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus westerdijkiae Unknown +AVI10276.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces lunaelactis MM91 +AVI26390.1 Bacteria Pseudomonadati Tectimicrobiota Entotheonellia Entotheonellales Entotheonellaceae Entotheonella Entotheonella serta Unknown +AVI26393.1 Bacteria Pseudomonadati Tectimicrobiota Entotheonellia Entotheonellales Entotheonellaceae Entotheonella Entotheonella serta Unknown +AVR48535.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Aphanizomenonaceae Cuspidothrix Cuspidothrix issatschenkoi CHARLIE-1 +AVV61987.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. ID38640 Unknown +AWI62626.1 Bacteria Pseudomonadati Myxococcota Myxococcia Myxococcales Archangiaceae Cystobacter Cystobacter sp. Cb vi35 +AWI62627.1 Bacteria Pseudomonadati Myxococcota Myxococcia Myxococcales Archangiaceae Cystobacter Cystobacter sp. Cb vi35 +AWI62628.1 Bacteria Pseudomonadati Myxococcota Myxococcia Myxococcales Archangiaceae Cystobacter Cystobacter sp. Cb vi35 +AWI62629.1 Bacteria Pseudomonadati Myxococcota Myxococcia Myxococcales Archangiaceae Cystobacter Cystobacter sp. Cb vi35 +AWS21276.1|AZY92000.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces armeniacus DSM 19369 +AWX24482.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces conglobatus ATCC 31005 +AWX24488.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces conglobatus ATCC 31005 +AXA20090.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Burkholderiaceae Burkholderia Burkholderia gladioli Lv-StB +AXA20091.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Burkholderiaceae Burkholderia Burkholderia gladioli Lv-StB +AXA91301.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Oxalobacteraceae Massilia Massilia sp. YMA4 +AXA91302.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Oxalobacteraceae Massilia Massilia sp. YMA4 +AXA94654.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Oxalobacteraceae Massilia Massilia sp. YMA4 +AXG22420.1 Bacteria Bacillati Actinomycetota Actinomycetes Mycobacteriales Nocardiaceae Nocardia Nocardia argentinensis ATCC 31306 +AXM42922.1 Bacteria Pseudomonadati Myxococcota Myxococcia Myxococcales Myxococcaceae Pyxidicoccus Pyxidicoccus fallax And48 +AXM42949.1 Bacteria Pseudomonadati Myxococcota Myxococcia Myxococcales Myxococcaceae Myxococcus Myxococcus fulvus SBMx132 +AXM43052.1 Bacteria Pseudomonadati Myxococcota Myxococcia Myxococcales Myxococcaceae Myxococcus Myxococcus sp. MCy10608 +AXM43064.1 Bacteria Pseudomonadati Myxococcota Myxococcia Myxococcales Myxococcaceae Myxococcus Myxococcus sp. MCy10608 +AXN93575.1|AXN93584.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Nostocaceae Cylindrospermum Cylindrospermum alatosporum CCALA 994 +AXN93580.1|AXN93589.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Nostocaceae Cylindrospermum Cylindrospermum alatosporum CCALA 994 +AXN93581.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Nostocaceae Cylindrospermum Cylindrospermum moravicum CCALA 993 +AXN93582.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Nostocaceae Cylindrospermum Cylindrospermum moravicum CCALA 993 +AXN93590.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Nostocaceae Cylindrospermum Cylindrospermum alatosporum CCALA 994 +AXN93591.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Nostocaceae Cylindrospermum Cylindrospermum alatosporum CCALA 994 +AXN93592.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Nostocaceae Anabaena Anabaena minutissima UTEX B 1613 +AXN93601.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Nostocaceae Anabaena Anabaena minutissima UTEX B 1613 +AXN93602.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Nostocaceae Anabaena Anabaena minutissima UTEX B 1613 +AXN93603.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Nostocaceae Anabaena Anabaena minutissima UTEX B 1613 +AXN93605.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Nostocaceae Anabaena Anabaena sp. UHCC-0399 +AXN93613.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Nostocaceae Anabaena Anabaena sp. UHCC-0399 +AXN93614.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Nostocaceae Anabaena Anabaena sp. UHCC-0399 +AXN93614.1*AXN93615.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Nostocaceae Anabaena Anabaena sp. UHCC-0399 +AXN93615.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Nostocaceae Anabaena Anabaena sp. UHCC-0399 +AXN93616.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Nostocaceae Anabaena Anabaena sp. UHCC-0399 +AYA22318.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Amycolatopsis Amycolatopsis keratiniphila NRRL B24117 +AYA22333.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Amycolatopsis Amycolatopsis keratiniphila NRRL B24117 +AYA22334.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Amycolatopsis Amycolatopsis keratiniphila NRRL B24117 +AYA22335.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Amycolatopsis Amycolatopsis keratiniphila NRRL B24117 +AYA22336.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Amycolatopsis Amycolatopsis keratiniphila NRRL B24117 +AYA44686.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Burkholderiaceae Burkholderia Burkholderia gladioli Lv-StA_HKI0739 +AYJ71720.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces paromomycinus NRRL:2455 +AYJ71721.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces paromomycinus NRRL:2455 +AZC86156.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Clavicipitaceae Metarhizium Metarhizium rileyi ARSEF 323 +AZH23792.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Oscillatoriales Microcoleaceae Okeania Okeania hirsuta PAB-10-Feb-10-1 +AZH23822.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Oscillatoriales Microcoleaceae Okeania Okeania hirsuta PAP-21-Jun-06-1 +AZL87944.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus flavus Unknown +AZM57022.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. WAC 01529 +AZM57023.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. WAC 01529 +AZM57024.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. WAC 01529 +AZM58102.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. WAC 01529 +AZZ09613.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Trichocomaceae Talaromyces Talaromyces variabilis HXQ-H-1 +B5X0I1 Bacteria Pseudomonadati Myxococcota Myxococcia Myxococcales Archangiaceae Stigmatella Stigmatella aurantiaca DW4/3-1 +B6F209.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus oryzae NBRC 4177 +B8RG41 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Burkholderiaceae Burkholderia Burkholderia contaminans MS14 +BAA00406.1 Bacteria Bacillati Bacillota Bacilli Bacillales Paenibacillaceae Brevibacillus Brevibacillus brevis Unknown +BAA02522.1 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus subtilis 168 trpC2 +BAA06146.1 Bacteria Bacillati Bacillota Bacilli Bacillales Paenibacillaceae Brevibacillus Brevibacillus brevis Nagano +BAA08846.1|P94873 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Lysobacterales Lysobacteraceae Lysobacter Lysobacter lactamgenus Unknown +BAA83992.1|Q9S1A9 Bacteria Bacillati Cyanobacteriota Cyanophyceae Chroococcales Microcystaceae Microcystis Microcystis aeruginosa Unknown +BAA83993.1|Q9S1A8 Bacteria Bacillati Cyanobacteriota Cyanophyceae Chroococcales Microcystaceae Microcystis Microcystis aeruginosa Unknown +BAA83994.1|Q9S1A7 Bacteria Bacillati Cyanobacteriota Cyanophyceae Chroococcales Microcystaceae Microcystis Microcystis aeruginosa Unknown +BAB12213.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Chroococcales Microcystaceae Microcystis Microcystis aeruginosa Unknown +BAB57094.1 Bacteria Bacillati Bacillota Bacilli Bacillales Staphylococcaceae Staphylococcus Staphylococcus aureus subsp. aureus Mu50 +BAB69698.1|Q93I56 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus subtilis Unknown +BAB69699.1|Q93I55 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus subtilis Unknown +BAB69700.1|Q93I54 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus subtilis Unknown +BAB94679.1 Bacteria Bacillati Bacillota Bacilli Bacillales Staphylococcaceae Staphylococcus Staphylococcus aureus subsp. aureus MW2 +BAC12912.1|Q8CV01 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Oceanobacillus Oceanobacillus iheyensis Unknown +BAC67534.2|Q84BQ6 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas sp. MIS38 Unknown +BAC67535.1|Q84BQ5 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas sp. MIS38 Unknown +BAC67536.1|Q84BQ4 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas sp. MIS38 Unknown +BAD55611.1|YP_116975.1 Bacteria Bacillati Actinomycetota Actinomycetes Mycobacteriales Nocardiaceae Nocardia Nocardia farcinica IFM 10152 +BAD55612.1|YP_116976.1 Bacteria Bacillati Actinomycetota Actinomycetes Mycobacteriales Nocardiaceae Nocardia Nocardia farcinica IFM 10152 +BAD55613.1|YP_116977.1 Bacteria Bacillati Actinomycetota Actinomycetes Mycobacteriales Nocardiaceae Nocardia Nocardia farcinica IFM 10152 +BAE06845.2 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Clavicipitaceae Epichloe Epichloe festucae Fl1 +BAE56606.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus oryzae RIB40 RIB 40 +BAE60013.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus oryzae RIB40 RIB 40 +BAE61264.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus oryzae RIB40 RIB 40 +BAE98151.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces lasalocidi ATCC 31180 +BAE98155.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces lasalocidi ATCC 31180 +BAE98156.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces lasalocidi ATCC 31180 +BAE98162.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces lasalocidi ATCC 31180 +BAF50711.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces virginiae Unknown +BAF50720.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces virginiae Unknown +BAF50727.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces virginiae Unknown +BAH04161.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces triostinicus Unknown +BAH04162.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces triostinicus Unknown +BAH04171.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces triostinicus Unknown +BAH04173.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces triostinicus Unknown +BAH22762.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Chroococcales Microcystaceae Microcystis Microcystis aeruginosa K-139 +BAH22763.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Chroococcales Microcystaceae Microcystis Microcystis aeruginosa K-139 +BAH22764.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Chroococcales Microcystaceae Microcystis Microcystis aeruginosa K-139 +BAH22765.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Chroococcales Microcystaceae Microcystis Microcystis aeruginosa K-139 +BAH23995.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus fumigatus BM939 +BAH33406.1 Bacteria Bacillati Actinomycetota Actinomycetes Mycobacteriales Nocardiaceae Rhodococcus Rhodococcus erythropolis PR4 PR4 (= NBRC 100887) +BAH33409.1 Bacteria Bacillati Actinomycetota Actinomycetes Mycobacteriales Nocardiaceae Rhodococcus Rhodococcus erythropolis PR4 PR4 (= NBRC 100887) +BAH43764.1 Bacteria Bacillati Bacillota Bacilli Bacillales Paenibacillaceae Brevibacillus Brevibacillus brevis NBRC 100599 NBRC 100599 (= 47) +BAH43765.1 Bacteria Bacillati Bacillota Bacilli Bacillales Paenibacillaceae Brevibacillus Brevibacillus brevis NBRC 100599 NBRC 100599 (= 47) +BAH43766.1 Bacteria Bacillati Bacillota Bacilli Bacillales Paenibacillaceae Brevibacillus Brevibacillus brevis NBRC 100599 NBRC 100599 (= 47) +BAI43678.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus flavus Unknown +BAI63283.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. SNA15896 +BAI63284.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. SNA15896 +BAI63288.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. SNA15896 +BAI63289.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. SNA15896 +BAL15718.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces rochei NBRC 12908 +BAL15732.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces rochei NBRC 12908 +BAN91483.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus japonicus Unknown +BAO73252.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Cordycipitaceae Lecanicillium Lecanicillium sp. HF627 +BAO84861.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces melanovinaceus DO-52 +BAO84866.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces melanovinaceus DO-52 +BAO84868.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces melanovinaceus DO-52 +BAP05589.1 Bacteria Pseudomonadati Tectimicrobiota Entotheonellia Entotheonellales Entotheonellaceae Entotheonella uncultured Entotheonella sp. Unknown +BAP05590.1 Bacteria Pseudomonadati Tectimicrobiota Entotheonellia Entotheonellales Entotheonellaceae Entotheonella uncultured Entotheonella sp. Unknown +BAP05591.1 Bacteria Pseudomonadati Tectimicrobiota Entotheonellia Entotheonellales Entotheonellaceae Entotheonella uncultured Entotheonella sp. Unknown +BAP05596.1 Bacteria Pseudomonadati Tectimicrobiota Entotheonellia Entotheonellales Entotheonellaceae Entotheonella uncultured Entotheonella sp. Unknown +BAP05597.1 Bacteria Pseudomonadati Tectimicrobiota Entotheonellia Entotheonellales Entotheonellaceae Entotheonella uncultured Entotheonella sp. Unknown +BAP16684.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. Sp080513GE-23 +BAP16689.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. Sp080513GE-23 +BAP16693.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. Sp080513GE-23 +BAP16697.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. Sp080513GE-23 +BAP16699.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. Sp080513GE-23 +BAR40283.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Nectriaceae Fusarium Fusarium sp. FN080326 +BAV19380.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Stachybotryaceae Stachybotrys Stachybotrys bisbyi PYH05-7 +BAV56002.1 Bacteria Bacillati Actinomycetota Actinomycetes Streptosporangiales Thermomonosporaceae Actinomadura Actinomadura fulva subsp. indica ATCC 53714 +BAV56017.1 Bacteria Bacillati Actinomycetota Actinomycetes Streptosporangiales Thermomonosporaceae Actinomadura Actinomadura fulva subsp. indica ATCC 53714 +BAV56270.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Lysobacterales Lysobacteraceae Lysobacter Lysobacter sp. RH2180-5 +BAV56271.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Lysobacterales Lysobacteraceae Lysobacter Lysobacter sp. RH2180-5 +BAV57443.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. SANK 60404 +BAV57451.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. SANK 60404 +BAW27693.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. SoC090715LN-17 +BAW32322.1 Bacteria Pseudomonadati Tectimicrobiota Entotheonellia Entotheonellales Entotheonellaceae Entotheonella uncultured Entotheonella sp. Unknown +BAW32323.1 Bacteria Pseudomonadati Tectimicrobiota Entotheonellia Entotheonellales Entotheonellaceae Entotheonella uncultured Entotheonella sp. Unknown +BAW32324.1 Bacteria Pseudomonadati Tectimicrobiota Entotheonellia Entotheonellales Entotheonellaceae Entotheonella uncultured Entotheonella sp. Unknown +BAW32332.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Chroococcales Microcystaceae Microcystis Microcystis aeruginosa NIES-87 +BAW32333.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Chroococcales Microcystaceae Microcystis Microcystis aeruginosa NIES-87 +BAW32334.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Chroococcales Microcystaceae Microcystis Microcystis aeruginosa NIES-87 +BAX64244.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. MSC090213JE08 +BAX64246.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. MSC090213JE08 +BAX64247.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. MSC090213JE08 +BAX89998.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Kibdelosporangium Kibdelosporangium sp. AK-AA56 +BAX89999.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Kibdelosporangium Kibdelosporangium sp. AK-AA56 +BAX90000.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Kibdelosporangium Kibdelosporangium sp. AK-AA56 +BAZ95823.1 Eukaryota Fungi Ascomycota Dothideomycetes Pleosporales Pleosporaceae Curvularia Curvularia pallescens DSM 62482 +BBA20967.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces atratus Unknown +BBA21068.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces avermitilis KA-320 +BBA21071.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces avermitilis KA-320 +BBA21073.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces avermitilis KA-320 +BBB04327.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Penicillium Penicillium simplicissimum Unknown +BBC43184.1 Eukaryota Fungi Ascomycota Dothideomycetes Pleosporales Pyrenochaetopsidaceae Pyrenochaetopsis Pyrenochaetopsis sp. RK10-F058 +BBC83957.1 Eukaryota Fungi Ascomycota Dothideomycetes Pleosporales Pleosporaceae Curvularia Curvularia clavata BAUA-2787 +BBD17741.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. ML55 +BBD17745.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. ML55 +BBD17759.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces orinoci NBRC 13466 +BBD17766.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces orinoci NBRC 13466 +BBE36469.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. SoC090715LN-16 +BBF25314.1|sp_A0A455R7E6.1_ASCB_ACREG Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales None Acremonium Acremonium egyptiacum F-1392 +BBG06551.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. NCIMB 40513 +BBG06561.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. NCIMB 40513 +BBH43485.1 Eukaryota Fungi Basidiomycota Agaricomycetes Agaricales Omphalotaceae Neonothopanus Neonothopanus nambi Unknown +BBQ09587.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Nectriaceae Fusarium Fusarium sp. RK97-94 +BBU42014.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Clavicipitaceae Epichloe Epichloe festucae Unknown +BCJ07529.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas sp. RtIB026 +BCJ07531.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas sp. RtIB026 +BCJ07532.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas sp. RtIB026 +BCJ07533.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas sp. RtIB026 +BCJ07599.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas sp. RtIB026 +BCJ07600.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas sp. RtIB026 +BFT43997.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Penicillium Penicillium sumatraense Unknown +BGRAMDRAFT_RS22640 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Burkholderiaceae Paraburkholderia Paraburkholderia graminis C4D1M +BN849_0052030 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Nectriaceae Fusarium Fusarium pseudograminearum CS5834 +BS329_14150 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Amycolatopsis Amycolatopsis coloradensis NRRL 3218 +BS330_28385 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Amycolatopsis Amycolatopsis keratiniphila DSM 44409 +BolH Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Burkholderiaceae Burkholderia Burkholderia gladioli BCC0238 +BolO Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Burkholderiaceae Burkholderia Burkholderia gladioli BCC0238 +C0JRF0 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus cereus UW85 +C0LTL8 Bacteria Bacillati Actinomycetota Actinomycetes Streptosporangiales Streptosporangiaceae Streptosporangium Streptosporangium sibiricum DSM 44039 +CAA06323.1|Q45295 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus licheniformis Unknown +CAA06324.1|O69246 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus licheniformis Unknown +CAA09819.1|O87704 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus subtilis Unknown +CAA11794.1|O52819 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Amycolatopsis Amycolatopsis orientalis Unknown +CAA11795.1|O52820 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Amycolatopsis Amycolatopsis orientalis Unknown +CAA11796.1|O52821 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Amycolatopsis Amycolatopsis orientalis Unknown +CAA11962.1|O76858 Eukaryota Metazoa Arthropoda Insecta Diptera Drosophilidae Drosophila Drosophila melanogaster Unknown +CAA38195.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Penicillium Penicillium chrysogenum CMI 314652 +CAA40561.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Amycolatopsis Amycolatopsis lactamdurans var LC 411 +CAA43838.1 Bacteria Bacillati Bacillota Bacilli Bacillales Paenibacillaceae Brevibacillus Brevibacillus brevis ATCC 9999 +CAA49818.1 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus subtilis W168 derivative of JH642 +CAA51561.1|P39581.1 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus subtilis subsp. subtilis str. 168 +CAA55749.1|Q54356 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces lincolnensis Unknown +CAA60461.1|Q54298 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces hygroscopicus Unknown +CAA67248.1|Q54959 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces pristinaespiralis Unknown +CAA67249.1|O07944 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces pristinaespiralis Unknown +CAA71336.1|O33743 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. Unknown +CAA72310.1|O05647 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces virginiae Unknown +CAA79245.2 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Nectriaceae Fusarium Fusarium scirpi Lambotte et Fautrey +CAA82227.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Ophiocordycipitaceae Tolypocladium Tolypocladium inflatum ATCC 34921 +CAA84360.1 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus subtilis subsp. subtilis str. 168 +CAA84361.1 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus subtilis subsp. subtilis str. 168 +CAA84363.1 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus subtilis subsp. subtilis str. 168 +CAA84364.1|P94460 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus subtilis Unknown +CAB13715.1 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus subtilis subsp. subtilis str. 168 +CAB15186.3 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus subtilis subsp. subtilis str. 168 +CAB38084.1|Q9Z5F4 Bacteria Pseudomonadati Pseudomonadota Deltaproteobacteria Myxococcales Myxococcaceae Myxococcus Myxococcus xanthus Unknown +CAB38517.1|Q9Z4X5 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces coelicolor Unknown +CAB38518.1|Q9Z4X6 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces coelicolor Unknown +CAB39315.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Clavicipitaceae Claviceps Claviceps purpurea P1 +CAB53322.1|Q9RK14 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces coelicolor Unknown +CAB55600.1|Q9RLP6 Bacteria Bacillati Actinomycetota Actinomycetes Mycobacteriales Mycobacteriaceae Mycolicibacterium Mycolicibacterium smegmatis Unknown +CAC01604.1|Q9K5M1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Nostocaceae Anabaena Anabaena sp. 90 Unknown +CAC01606.1|Q9K5L9 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Nostocaceae Anabaena Anabaena sp. 90 Unknown +CAC17499.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces coelicolor A3(2) +CAC17500.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces coelicolor A3(2) +CAC48360.1|Q939Z1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Amycolatopsis Amycolatopsis balhimycina Unknown +CAC48361.1|Q939Z0 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Amycolatopsis Amycolatopsis balhimycina Unknown +CAC48362.1|Q939Y9 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Amycolatopsis Amycolatopsis balhimycina Unknown +CAC48369.1|Q939Y2 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Amycolatopsis Amycolatopsis balhimycina Unknown +CAD15508.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Burkholderiaceae Ralstonia Ralstonia pseudosolanacearum GMI1000 +CAD15513.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Burkholderiaceae Ralstonia Ralstonia pseudosolanacearum GMI1000 +CAD17792.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Burkholderiaceae Ralstonia Ralstonia pseudosolanacearum GMI1000 +CAD17793.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Burkholderiaceae Ralstonia Ralstonia pseudosolanacearum GMI1000 +CAD18570.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Burkholderiaceae Ralstonia Ralstonia pseudosolanacearum GMI1000 +CAD28788.1|Q8J0L6.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Clavicipitaceae Claviceps Claviceps purpurea P1 +CAD29794.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Oscillatoriales Microcoleaceae Planktothrix Planktothrix agardhii NIVA-CYA 126/8 +CAD29795.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Oscillatoriales Microcoleaceae Planktothrix Planktothrix agardhii NIVA-CYA 126/8 +CAD29797.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Oscillatoriales Microcoleaceae Planktothrix Planktothrix agardhii NIVA-CYA 126/8 +CAD29798.1|Q8G982 Bacteria Bacillati Cyanobacteriota Cyanophyceae Oscillatoriales Microcoleaceae Planktothrix Planktothrix agardhii Unknown +CAD29799.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Oscillatoriales Microcoleaceae Planktothrix Planktothrix agardhii NIVA-CYA 126/8 +CAD32904.2 Bacteria Bacillati Actinomycetota Actinomycetes Micromonosporales Micromonosporaceae Actinoplanes Actinoplanes friuliensis Unknown +CAD55498.1|Q8CJX2 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces coelicolor Unknown +CAD70194.1|Q83Y49 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas syringae Unknown +CAD70195.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas syringae B301D-R +CAD89774.1|Q70P97 Bacteria Pseudomonadati Pseudomonadota Deltaproteobacteria Myxococcales Archangiaceae Melittangium Melittangium lichenicola Unknown +CAD89775.1 Bacteria Pseudomonadati Myxococcota Myxococcia Myxococcales Archangiaceae Melittangium Melittangium lichenicola Unknown +CAD89778.1 Bacteria Pseudomonadati Myxococcota Myxococcia Myxococcales Archangiaceae Melittangium Melittangium lichenicola Unknown +CAD91211.1|Q7WZ75 Bacteria Bacillati Actinomycetota Actinomycetes Streptosporangiales Streptosporangiaceae Nonomuraea Nonomuraea gerenzanensis Unknown +CAD91212.1|Q7WZ74 Bacteria Bacillati Actinomycetota Actinomycetes Streptosporangiales Streptosporangiaceae Nonomuraea Nonomuraea gerenzanensis Unknown +CAD91220.1|Q7WZ66 Bacteria Bacillati Actinomycetota Actinomycetes Streptosporangiales Streptosporangiaceae Nonomuraea Nonomuraea gerenzanensis Unknown +CAD91221.1|Q7WZ65 Bacteria Bacillati Actinomycetota Actinomycetes Streptosporangiales Streptosporangiaceae Nonomuraea Nonomuraea gerenzanensis Unknown +CAD92849.1 Bacteria Bacillati Bacillota Bacilli Bacillales Paenibacillaceae Brevibacillus Brevibacillus brevis ATCC 8185 +CAD92850.1 Bacteria Bacillati Bacillota Bacilli Bacillales Paenibacillaceae Brevibacillus Brevibacillus brevis ATCC 8185 +CAD92851.1 Bacteria Bacillati Bacillota Bacilli Bacillales Paenibacillaceae Brevibacillus Brevibacillus brevis ATCC 8185 +CAD92852.1 Bacteria Bacillati Bacillota Bacilli Bacillales Paenibacillaceae Brevibacillus Brevibacillus brevis ATCC 8185 +CAE02630.1 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus velezensis FZB42 +CAE02631.1 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus velezensis FZB42 +CAE11249.1 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus velezensis FZB42 +CAE14171.1|WP_011146143.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Morganellaceae None Photorhabdus Unknown +CAE14173.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Morganellaceae Photorhabdus Photorhabdus laumondii subsp. laumondii TTO1 +CAE14766.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Morganellaceae Photorhabdus Photorhabdus laumondii subsp. laumondii TTO1 +CAE15497.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Morganellaceae Photorhabdus Photorhabdus laumondii subsp. laumondii TTO1 +CAE15637.1|WP_011147463.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Morganellaceae None Photorhabdus Unknown +CAE16560.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Morganellaceae Photorhabdus Photorhabdus laumondii subsp. laumondii TTO1 +CAE52342.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Lysobacterales Lysobacteraceae Xanthomonas Xanthomonas albilineans Xa23R1 +CAE53350.1|Q70AZ9 Bacteria Bacillati Actinomycetota Actinomycetes Micromonosporales Micromonosporaceae Actinoplanes Actinoplanes teichomyceticus Unknown +CAE53351.1|Q70AZ8 Bacteria Bacillati Actinomycetota Actinomycetes Micromonosporales Micromonosporaceae Actinoplanes Actinoplanes teichomyceticus Unknown +CAE53352.1|Q70AZ7 Bacteria Bacillati Actinomycetota Actinomycetes Micromonosporales Micromonosporaceae Actinoplanes Actinoplanes teichomyceticus Unknown +CAE53353.1|Q70AZ6 Bacteria Bacillati Actinomycetota Actinomycetes Micromonosporales Micromonosporaceae Actinoplanes Actinoplanes teichomyceticus Unknown +CAF05647.1|Q5ZPB0 Bacteria Pseudomonadati Pseudomonadota Deltaproteobacteria Myxococcales Archangiaceae Archangium Archangium disciforme Unknown +CAG15009.1 Bacteria Bacillati Actinomycetota Actinomycetes Micromonosporales Micromonosporaceae Actinoplanes Actinoplanes teichomyceticus Unknown +CAG15010.1 Bacteria Bacillati Actinomycetota Actinomycetes Micromonosporales Micromonosporaceae Actinoplanes Actinoplanes teichomyceticus Unknown +CAG15011.1 Bacteria Bacillati Actinomycetota Actinomycetes Micromonosporales Micromonosporaceae Actinoplanes Actinoplanes teichomyceticus Unknown +CAG15012.1 Bacteria Bacillati Actinomycetota Actinomycetes Micromonosporales Micromonosporaceae Actinoplanes Actinoplanes teichomyceticus Unknown +CAG69514.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Moraxellales Moraxellaceae Acinetobacter Acinetobacter baylyi ADP1 +CAG69516.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Moraxellales Moraxellaceae Acinetobacter Acinetobacter baylyi ADP1 +CAH37575.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Burkholderiaceae Burkholderia Burkholderia pseudomallei K96243 +CAI59268.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Clavicipitaceae Claviceps Claviceps purpurea P1 +CAI94718.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces rubradiris NRRL 3061 +CAJ18237.2 Bacteria Bacillati Actinomycetota Actinomycetes Micromonosporales Micromonosporaceae Actinoplanes Actinoplanes friuliensis Unknown +CAJ21198.2 Bacteria Bacillati Cyanobacteriota Cyanophyceae Oscillatoriales Microcoleaceae Planktothrix Planktothrix agardhii NIVA-CYA 126 Unknown +CAJ34374.1 Bacteria Bacillati Actinomycetota Actinomycetes Micromonosporales Micromonosporaceae Micromonospora Micromonospora sp. ML1 Unknown +CAJ34375.1 Bacteria Bacillati Actinomycetota Actinomycetes Micromonosporales Micromonosporaceae Micromonospora Micromonospora sp. ML1 Unknown +CAJ45636.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Vibrionales Vibrionaceae Vibrio Vibrio anguillarum RV22 +CAJ45639.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Vibrionales Vibrionaceae Vibrio Vibrio anguillarum RV22 +CAJ46691.1|Q0VZ71 Bacteria Pseudomonadati Pseudomonadota Deltaproteobacteria Myxococcales Polyangiaceae Chondromyces Chondromyces crocatus Unknown +CAJ46692.1 Bacteria Pseudomonadati Myxococcota Polyangia Polyangiales Polyangiaceae Chondromyces Chondromyces crocatus Cm c5 +CAJ76286.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Enterobacteriaceae Escherichia Escherichia coli IHE3034 +CAJ76289.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Enterobacteriaceae Escherichia Escherichia coli IHE3034 +CAJ76290.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Enterobacteriaceae Escherichia Escherichia coli IHE3034 +CAJ76292.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Enterobacteriaceae Escherichia Escherichia coli IHE3034 +CAJ76298.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Enterobacteriaceae Escherichia Escherichia coli IHE3034 +CAJ77695.1 Bacteria Bacillati Actinomycetota Actinomycetes Mycobacteriales Mycobacteriaceae Mycobacteroides Mycobacteroides chelonae type strain:CIP104535=ATCC35752 +CAJ77696.1 Bacteria Bacillati Actinomycetota Actinomycetes Mycobacteriales Mycobacteriaceae Mycobacteroides Mycobacteroides chelonae type strain:CIP104535=ATCC35752 +CAJ77715.1 Bacteria Bacillati Actinomycetota Actinomycetes Mycobacteriales Mycobacteriaceae Mycobacteroides Mycobacteroides abscessus type strain:CIP104536=ATCC19977 +CAJ77716.1 Bacteria Bacillati Actinomycetota Actinomycetes Mycobacteriales Mycobacteriaceae Mycobacteroides Mycobacteroides abscessus type strain:CIP104536=ATCC19977 +CAJ88610.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces ambofaciens ATCC 23877 +CAJ88630.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces ambofaciens ATCC 23877 +CAJ96468.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Burkholderiaceae Cupriavidus Cupriavidus necator H16 +CAJ96470.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Burkholderiaceae Cupriavidus Cupriavidus necator H16 +CAJ96471.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Burkholderiaceae Cupriavidus Cupriavidus necator H16 +CAJ96472.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Burkholderiaceae Cupriavidus Cupriavidus necator H16 +CAK15814.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas entomophila L48 +CAK15815.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas entomophila L48 +CAL69597.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Cordycipitaceae Beauveria Beauveria bassiana Unknown +CAM02313.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Saccharopolyspora Saccharopolyspora erythraea NRRL 2338 +CAM56770.1 Bacteria Bacillati Actinomycetota Actinomycetes Micromonosporales Micromonosporaceae Actinoplanes Actinoplanes friuliensis Unknown +CAM56771.1 Bacteria Bacillati Actinomycetota Actinomycetes Micromonosporales Micromonosporaceae Actinoplanes Actinoplanes friuliensis Unknown +CAM59606.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Oscillatoriales Microcoleaceae Planktothrix Planktothrix agardhii NIVA-CYA 126 Unknown +CAN89633.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces collinus Tu 365 +CAN89638.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces collinus Tu 365 +CAO91861.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Penicillium Penicillium expansum Unknown +CAP20363.1 Bacteria Bacillati Bacillota Bacilli Lactobacillales Streptococcaceae Streptococcus Streptococcus equi subsp. equi 4047 +CAP20364.1 Bacteria Bacillati Bacillota Bacilli Lactobacillales Streptococcaceae Streptococcus Streptococcus equi subsp. equi 4047 +CAP93139.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Penicillium Penicillium rubens Wisconsin 54-1255 +CAP96445.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Penicillium Penicillium rubens Wisconsin 54-1255 +CAQ18831.1 Bacteria Pseudomonadati Myxococcota Polyangia Polyangiales Polyangiaceae Chondromyces Chondromyces crocatus Cm c5 +CAQ18839.1 Bacteria Pseudomonadati Myxococcota Polyangia Polyangiales Polyangiaceae Chondromyces Chondromyces crocatus Cm c5 +CAQ43084.1 Bacteria Pseudomonadati Myxococcota Polyangia Polyangiales Polyangiaceae Chondromyces Chondromyces crocatus Cm c5 +CAQ71827.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Burkholderiaceae Cupriavidus Cupriavidus taiwanensis LMG 19424 +CAQ71828.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Burkholderiaceae Cupriavidus Cupriavidus taiwanensis LMG 19424 +CAQ71829.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Burkholderiaceae Cupriavidus Cupriavidus taiwanensis LMG 19424 +CAY48788.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas fluorescens SBW25 +CAY48789.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas fluorescens SBW25 +CBA63660.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. ATCC 700974 +CBA63680.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. ATCC 700974 +CBF73453.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus nidulans FGSC A4 +CBF76036.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus nidulans FGSC A4 +CBF76038.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus nidulans FGSC A4 +CBF77087.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus nidulans FGSC A4 +CBF80711.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus nidulans FGSC A4 +CBF82791.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus nidulans FGSC A4 +CBF87069.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus nidulans FGSC A4 +CBF87869.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus nidulans FGSC A4 +CBG67531.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces scabiei 87.22 +CBG67541.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces scabiei 87.22 +CBG75492.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces scabiei 87.22 +CBJ79718.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Morganellaceae Xenorhabdus Xenorhabdus bovienii SS-2004 +CBJ79915.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Morganellaceae Xenorhabdus Xenorhabdus bovienii SS-2004 +CBJ79916.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Morganellaceae Xenorhabdus Xenorhabdus bovienii SS-2004 +CBJ90082.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Morganellaceae Xenorhabdus Xenorhabdus nematophila ATCC 19061 +CBJ90287.1|WP_013184317.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Morganellaceae Xenorhabdus Xenorhabdus nematophila Unknown +CBJ90288.1|WP_013184318.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Morganellaceae Xenorhabdus Xenorhabdus nematophila Unknown +CBJ90289.1|WP_013184319.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Morganellaceae Xenorhabdus Xenorhabdus nematophila Unknown +CBK62746.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Alteromonadales Pseudoalteromonadaceae Pseudoalteromonas Pseudoalteromonas sp. SANK 73390 +CBL93716.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. L-49973 +CBL93718.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. L-49973 +CBL93720.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. L-49973 +CBL93723.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. L-49973 +CBW54672.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces cinnabarigriseus JS360 +CBW75451.1|QIH29229.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Burkholderiaceae Mycetohabitans Mycetohabitans rhizoxinica HKI454 +CBW75452.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Burkholderiaceae Mycetohabitans Mycetohabitans rhizoxinica HKI 454 +CBW75453.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Burkholderiaceae Mycetohabitans Mycetohabitans rhizoxinica HKI 454 +CBW75453.1*CBW75452.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Burkholderiaceae Mycetohabitans Mycetohabitans rhizoxinica HKI 454 +CBW75455.1|QIH29226.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Burkholderiaceae Mycetohabitans Mycetohabitans rhizoxinica HKI454 +CBZ42140.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces himastatinicus ATCC 53653 type strain: ATCC 53653 +CBZ42143.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces himastatinicus ATCC 53653 type strain: ATCC 53653 +CBZ42145.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces himastatinicus ATCC 53653 type strain: ATCC 53653 +CBZ42146.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces himastatinicus ATCC 53653 type strain: ATCC 53653 +CCA29202.1 Bacteria Pseudomonadati Myxococcota Myxococcia Myxococcales Myxococcaceae Myxococcus Myxococcus xanthus DK897 +CCA29203.1 Bacteria Pseudomonadati Myxococcota Myxococcia Myxococcales Myxococcaceae Myxococcus Myxococcus xanthus DK897 +CCA53797.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces venezuelae ATCC 10712 +CCA53799.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces venezuelae ATCC 10712 +CCA53804.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces venezuelae ATCC 10712 +CCA89326.1 Bacteria Pseudomonadati Myxococcota Myxococcia Myxococcales Archangiaceae Stigmatella Stigmatella aurantiaca Sg a15 +CCA89328.1 Bacteria Pseudomonadati Myxococcota Myxococcia Myxococcales Archangiaceae Stigmatella Stigmatella aurantiaca Sg a15 +CCB53264.1 Bacteria Bacillati Bacillota Bacilli Bacillales Staphylococcaceae Staphylococcus Staphylococcus lugdunensis N920143 +CCB53266.1 Bacteria Bacillati Bacillota Bacilli Bacillales Staphylococcaceae Staphylococcus Staphylococcus lugdunensis N920143 +CCB53267.1 Bacteria Bacillati Bacillota Bacilli Bacillales Staphylococcaceae Staphylococcus Staphylococcus lugdunensis N920143 +CCB53269.1 Bacteria Bacillati Bacillota Bacilli Bacillales Staphylococcaceae Staphylococcus Staphylococcus lugdunensis N920143 +CCC55921.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. CS40 +CCC55922.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. CS40 +CCE28989.1|sp_M1WCQ3.1_TCPP_CLAP2 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Clavicipitaceae Claviceps Claviceps purpurea 20.1 +CCE30237.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Clavicipitaceae Claviceps Claviceps purpurea 20.1 +CCJ67636.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas costantinii DSM 16734 +CCJ67637.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas costantinii DSM 16734 +CCJ67638.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas costantinii DSM 16734 +CCJ67639.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas costantinii DSM 16734 +CCJ67640.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas costantinii DSM 16734 +CCJ67645.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Oxalobacteraceae Janthinobacterium Janthinobacterium agaricidamnosum DSM 9628 +CCJ67646.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Oxalobacteraceae Janthinobacterium Janthinobacterium agaricidamnosum DSM 9628 +CCJ67647.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Oxalobacteraceae Janthinobacterium Janthinobacterium agaricidamnosum DSM 9628 +CCJ67648.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Oxalobacteraceae Janthinobacterium Janthinobacterium agaricidamnosum DSM 9628 +CCM44336.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Yersiniaceae Serratia Serratia plymuthica RVH1 +CCM44337.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Yersiniaceae Serratia Serratia plymuthica RVH1 +CCP42824.1 Bacteria Bacillati Actinomycetota Actinomycetes Mycobacteriales Mycobacteriaceae Mycobacterium Mycobacterium tuberculosis H37Rv +CCP42826.1 Bacteria Bacillati Actinomycetota Actinomycetes Mycobacteriales Mycobacteriaceae Mycobacterium Mycobacterium tuberculosis H37Rv +CCP45167.1|O05819 Bacteria Bacillati Actinomycetota Actinomycetes Mycobacteriales Mycobacteriaceae Mycobacterium Mycobacterium tuberculosis Unknown +CCT73878.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Nectriaceae Fusarium Fusarium fujikuroi IMI 58289 +CDF96614.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas sp. SHC52 +CDG12864.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Yersiniaceae Serratia Serratia marcescens subsp. marcescens Db11 +CDG12865.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Yersiniaceae Serratia Serratia marcescens subsp. marcescens Db11 +CDG17980.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Morganellaceae Xenorhabdus Xenorhabdus doucetiae FRM16 +CDG17981.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Morganellaceae Xenorhabdus Xenorhabdus doucetiae FRM16 +CDG17982.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Morganellaceae Xenorhabdus Xenorhabdus doucetiae FRM16 +CDG76957.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Enterobacteriaceae Klebsiella Klebsiella oxytoca AHC-6 +CDG76959.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Enterobacteriaceae Klebsiella Klebsiella oxytoca AHC-6 +CDN62030.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Burkholderiaceae Burkholderia Burkholderia cenocepacia H111 +CEO59272.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Penicillium Penicillium brasilianum Unknown +CFJ82030.1 Bacteria Bacillati Actinomycetota Actinomycetes Mycobacteriales Mycobacteriaceae Mycobacterium Mycobacterium tuberculosis 2251Y +CRG85572.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Trichocomaceae Talaromyces Talaromyces islandicus Unknown +CUX79060.1 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Niallia Niallia circulans ATCC 31805 +CUX79061.1 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Niallia Niallia circulans ATCC 31805 +CUX79062.1 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Niallia Niallia circulans ATCC 31805 +CUX96954.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces chromofuscus ATCC 49982 +CZT62784.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Oscillatoriales Microcoleaceae Planktothrix Planktothrix serta PCC 8927 +CZT62785.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Oscillatoriales Microcoleaceae Planktothrix Planktothrix serta PCC 8927 +CZT62792.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Oscillatoriales Microcoleaceae Planktothrix Planktothrix serta PCC 8927 +CZT62794.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Oscillatoriales Microcoleaceae Planktothrix Planktothrix serta PCC 8927 +ClsI Eukaryota Fungi Ascomycota Dothideomycetes Cladosporiales Cladosporiaceae Cladosporium Cladosporium sp. SW67 +D581_RS01000000137735 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. CNB091 +DAB41476.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. CNB091 +DAB41477.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. CNB091 +DAB41478.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. CNB091 +DAB41479.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. CNB091 +DAB41484.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. CNB091 +DAB41661.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Hypocreaceae Escovopsis Escovopsis weberi Unknown +DAB41917.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Hapalosiphonaceae Fischerella Fischerella sp. PCC 9339 +DAC74137.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. CB03234 CB003234 +DAC76731.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. NRRL F-4335 +DAC76734.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. NRRL F-4335 +DAC76736.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. NRRL F-4335 +DAC82014.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria None None None uncultured Gammaproteobacteria bacterium Unknown +DAC82026.1 Bacteria Pseudomonadati Kiritimatiellota None None None None Kiritimatiellota bacterium Unknown +DAC82028.1 Bacteria Pseudomonadati Kiritimatiellota None None None None Kiritimatiellota bacterium Unknown +DAD54486.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Lysobacterales Lysobacteraceae Xanthomonas Xanthomonas cannabis pv. cannabis NCPPB 3753 +DAD54574.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Nectriaceae Fusarium Fusarium equiseti Unknown +DAD54576.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Nectriaceae Fusarium Fusarium equiseti Unknown +DMA15_34345 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. WAC 01529 +DMH02_027320 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. WAC00631 +E0F75_025360 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. CB02980 +EAA62478.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus nidulans FGSC A4 +EAA67034.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus nidulans FGSC A4 +EAL85113.2 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus fumigatus Af293 +EAL86624.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus fumigatus Af293 +EAL88817.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus fumigatus Af293 +EAL89046.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus fumigatus Af293 +EAL89049.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus fumigatus Af293 +EAL89229.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus fumigatus Af293 +EAL92291.2 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus fumigatus Af293 +EAQ93004.1|XP_001220460.1 Eukaryota Fungi Ascomycota Sordariomycetes Sordariales Chaetomiaceae Chaetomium Chaetomium globosum CBS 148.51 +EAT91803.2 Eukaryota Fungi Ascomycota Dothideomycetes Pleosporales Phaeosphaeriaceae Parastagonospora Parastagonospora nodorum SN15 +EAU29302.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus terreus NIH2624 +EAU31031.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus terreus NIH2624 +EAU35432.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus terreus NIH2624 +EAU36089.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus terreus NIH2624 +EAU36744.1|XP_001212648.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus terreus NIH2624 +EAU36837.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus terreus NIH2624 +EAU36966.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus terreus NIH2624 +EAU38971.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus terreus NIH2624 +EAU39346.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus terreus NIH2624 +EAW09117.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus clavatus NRRL 1 +EDU47082.1 Eukaryota Fungi Ascomycota Dothideomycetes Pleosporales Pleosporaceae Pyrenophora Pyrenophora tritici-repentis Pt-1C-BFP +EDY47118.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces clavuligerus ATCC 27064 +EED49862.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus flavus NRRL3357 +EFE73308.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces filamentosus NRRL 15998 +EFE73312.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces filamentosus NRRL 15998 +EFE73313.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces filamentosus NRRL 15998 +EFL02193.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. SPB78 +EFL06864.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. AA4 +EFL06865.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. AA4 +EFL06866.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. AA4 +EFL06867.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. AA4 +EFL06871.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. AA4 +EFY95969.1|EXU97982.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Clavicipitaceae Metarhizium Metarhizium robertsii ARSEF 2575 +EFY99276.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Clavicipitaceae Metarhizium Metarhizium robertsii ARSEF 23 +EGO23141.1 Eukaryota Fungi Basidiomycota Agaricomycetes Boletales Serpulaceae Serpula Serpula lacrymans var. lacrymans S7.9 +EGX43679.1 Eukaryota Fungi Ascomycota Orbiliomycetes Orbiliales Orbiliaceae Orbilia Orbilia oligospora ATCC 24927 +EGX96626.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Cordycipitaceae Cordyceps Cordyceps militaris CM01 +EGX96627.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Cordycipitaceae Cordyceps Cordyceps militaris CM01 +EHA27898.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus niger ATCC 1015 +EHA53213.1 Eukaryota Fungi Ascomycota Sordariomycetes Magnaporthales Pyriculariaceae Pyricularia Pyricularia oryzae 70-15 +EHA55860.1|sp_G4MVZ2.1_ACE1_PYRO7 Eukaryota Fungi Ascomycota Sordariomycetes Magnaporthales Pyriculariaceae Pyricularia Pyricularia oryzae 70-15 +EHK22005.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Hypocreaceae Trichoderma Trichoderma virens Gv29-8 +EJK79842.1 Bacteria Pseudomonadati Pseudomonadota Alphaproteobacteria Hyphomicrobiales Rhizobiaceae Rhizobium Rhizobium sp. AP16 +EJP62835.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Cordycipitaceae Beauveria Beauveria bassiana ARSEF 2860 +EKG15173.1 Eukaryota Fungi Ascomycota Dothideomycetes Botryosphaeriales Botryosphaeriaceae Macrophomina Macrophomina phaseolina MS6 +EKG15176.1 Eukaryota Fungi Ascomycota Dothideomycetes Botryosphaeriales Botryosphaeriaceae Macrophomina Macrophomina phaseolina MS6 +EKJ70673.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Nectriaceae Fusarium Fusarium pseudograminearum CS3096 +EMD85433.1 Eukaryota Fungi Ascomycota Dothideomycetes Pleosporales Pleosporaceae Bipolaris Bipolaris maydis C5 +EMD93665.1 Eukaryota Fungi Ascomycota Dothideomycetes Pleosporales Pleosporaceae Bipolaris Bipolaris maydis C5 +EME52974.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Amycolatopsis Amycolatopsis decaplanina DSM 44594 +EME52988.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Amycolatopsis Amycolatopsis decaplanina DSM 44594 +EME52989.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Amycolatopsis Amycolatopsis decaplanina DSM 44594 +EME52990.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Amycolatopsis Amycolatopsis decaplanina DSM 44594 +EOY45602.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces lividans 1326 +EPE34341.1 Eukaryota Fungi Ascomycota Leotiomycetes Helotiales Helotiaceae Glarea Glarea lozoyensis ATCC 20868 +EPS29069.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Penicillium Penicillium oxalicum 114-2 +EPS34234.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Penicillium Penicillium oxalicum 114-2 +ERG36782.1|WP_010369425.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Alteromonadales Pseudoalteromonadaceae Pseudoalteromonas Pseudoalteromonas piscicida Unknown +ERG36783.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Alteromonadales Pseudoalteromonadaceae Pseudoalteromonas Pseudoalteromonas piscicida JCM 20779 +ESU15173.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Nectriaceae Fusarium Fusarium graminearum PH-1 PH-1; NRRL 31084 +ESU17758.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Nectriaceae Fusarium Fusarium graminearum PH-1 PH-1; NRRL 31084 +ESU17760.1|XP_011325382.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Nectriaceae Fusarium Fusarium graminearum PH-1 PH-1; NRRL 31084 +ETR98599.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Hypocreaceae Trichoderma Trichoderma reesei RUT C-30 +ETS82484.1 Eukaryota Fungi Ascomycota Sordariomycetes Amphisphaeriales Sporocadaceae Pestalotiopsis Pestalotiopsis fici W106-1 +EWG54274.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Nectriaceae Fusarium Fusarium verticillioides 7600 +EWM63002.1 Bacteria Bacillati Actinomycetota Actinomycetes Micromonosporales Micromonosporaceae Micromonospora Micromonospora sp. M42 +EWM63005.1 Bacteria Bacillati Actinomycetota Actinomycetes Micromonosporales Micromonosporaceae Micromonospora Micromonospora sp. M42 +EWM63007.1 Bacteria Bacillati Actinomycetota Actinomycetes Micromonosporales Micromonosporaceae Micromonospora Micromonospora sp. M42 +EWS95122.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces filamentosus NRRL 11379 +EWS95124.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces filamentosus NRRL 11379 +EXU96269.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Clavicipitaceae Metarhizium Metarhizium robertsii ARSEF 2575 +EYB32861.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Nectriaceae Fusarium Fusarium graminearum CS3005 +EYE98744.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus ruber CBS 135680 +FAA01291.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus violaceofuscus CBS 115571 +FGSG_15673 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Nectriaceae Fusarium Fusarium graminearum PH-1 +Ga0173608_111474 Bacteria Pseudomonadati Bacteroidota Flavobacteriia Flavobacteriales Flavobacteriaceae Endobryopsis Endobryopsis kahalalidefaciens SB5 +Ga0173608_111498 Bacteria Pseudomonadati Bacteroidota Flavobacteriia Flavobacteriales Flavobacteriaceae Endobryopsis Endobryopsis kahalalidefaciens SB5 +Ga0173608_111792 Bacteria Pseudomonadati Bacteroidota Flavobacteriia Flavobacteriales Flavobacteriaceae Endobryopsis Endobryopsis kahalalidefaciens SB5 +Ga0173608_111989 Bacteria Pseudomonadati Bacteroidota Flavobacteriia Flavobacteriales Flavobacteriaceae Endobryopsis Endobryopsis kahalalidefaciens SB5 +Ga0173608_111990 Bacteria Pseudomonadati Bacteroidota Flavobacteriia Flavobacteriales Flavobacteriaceae Endobryopsis Endobryopsis kahalalidefaciens SB5 +Ga0173608_112008 Bacteria Pseudomonadati Bacteroidota Flavobacteriia Flavobacteriales Flavobacteriaceae Endobryopsis Endobryopsis kahalalidefaciens SB5 +Ga0173608_112053 Bacteria Pseudomonadati Bacteroidota Flavobacteriia Flavobacteriales Flavobacteriaceae Endobryopsis Endobryopsis kahalalidefaciens SB5 +Ga0173608_112187 Bacteria Pseudomonadati Bacteroidota Flavobacteriia Flavobacteriales Flavobacteriaceae Endobryopsis Endobryopsis kahalalidefaciens SB5 +Ga0173608_11674 Bacteria Pseudomonadati Bacteroidota Flavobacteriia Flavobacteriales Flavobacteriaceae Endobryopsis Endobryopsis kahalalidefaciens SB5 +Ga0173608_11675 Bacteria Pseudomonadati Bacteroidota Flavobacteriia Flavobacteriales Flavobacteriaceae Endobryopsis Endobryopsis kahalalidefaciens SB5 +Ga0173608_11676 Bacteria Pseudomonadati Bacteroidota Flavobacteriia Flavobacteriales Flavobacteriaceae Endobryopsis Endobryopsis kahalalidefaciens SB5 +KAF3404987.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Trichocomaceae Talaromyces Talaromyces pinophilus AR155 +KAF7597139.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus hancockii FRR 3425 +KAF7597140.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus hancockii FRR 3425 +KAL2700169.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Trichocomaceae Penicillium Penicillium crustosum PRB-2 +KFA69336.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Stachybotryaceae Stachybotrys Stachybotrys chlorohalonatus IBT 40285 +KFH48607.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Bionectriaceae Hapsidospora Hapsidospora chrysogenum ATCC 11550 +KFL51883.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Burkholderiaceae Burkholderia Burkholderia pyrrocinia Lyc2 +KFL51885.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Burkholderiaceae Burkholderia Burkholderia pyrrocinia Lyc2 +KFL51886.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Burkholderiaceae Burkholderia Burkholderia pyrrocinia Lyc2 +KFL51887.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Burkholderiaceae Burkholderia Burkholderia pyrrocinia Lyc2 +KIA75356.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus ustus 3.3904 +KIA75458.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus ustus 3.3904 +KIA75587.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus ustus 3.3904 +KIA75688.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus ustus 3.3904 +KKP04599.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Hypocreaceae Trichoderma Trichoderma harzianum T6776 +KPN90369.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas nunensis In5 +KPN90374.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas nunensis In5 +KPN90376.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas nunensis In5 +KPN93063.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas nunensis In5 +KPN93064.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas nunensis In5 +KPN93065.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas nunensis In5 +MBA5221218.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces griseoaurantiacus MBK6 +MBA5221219.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces griseoaurantiacus MBK6 +MBV7329455.1 Bacteria Bacillati Chloroflexota Chloroflexia Chloroflexales Chloroflexaceae None Chloroflexi bacterium TSY +MCC5025983.1 Bacteria Pseudomonadati Verrucomicrobiota Opitutia Opitutales Opitutaceae Synoicihabitans Synoicihabitans palmerolidicus Unknown +MCC5026027.1 Bacteria Pseudomonadati Verrucomicrobiota Opitutia Opitutales Opitutaceae Synoicihabitans Synoicihabitans palmerolidicus Unknown +MCC5036783.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. WAC00631 +MCC5036784.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. WAC00631 +MCC5036785.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. WAC00631 +MCC5036786.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. WAC00631 +NAO96317.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Oceanospirillales Halomonadaceae Halomonas Halomonas sp. MG34 +NAO96318.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Oceanospirillales Halomonadaceae Halomonas Halomonas sp. MG34 +NAO96319.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Oceanospirillales Halomonadaceae Halomonas Halomonas sp. MG34 +NAO96320.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Oceanospirillales Halomonadaceae Halomonas Halomonas sp. MG34 +NHN68324.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas fluorescens DSM 11579 +NHN68325.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas fluorescens DSM 11579 +NP_593102.1 Eukaryota Fungi Ascomycota Schizosaccharomycetes Schizosaccharomycetales Schizosaccharomycetaceae Schizosaccharomyces Schizosaccharomyces pombe 972h- +NSC20090.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces albus subsp. chlorinus NRRL B-24108 +NSC20093.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces albus subsp. chlorinus NRRL B-24108 +NSC20094.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces albus subsp. chlorinus NRRL B-24108 +NSC23530.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces albus subsp. chlorinus NRRL B-24108 +O30409.1 Bacteria Bacillati Bacillota Bacilli Bacillales Paenibacillaceae Brevibacillus Brevibacillus parabrevis Unknown +O66070 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus licheniformis Unknown +O69247 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus licheniformis Unknown +O86329 Bacteria Bacillati Actinomycetota Actinomycetes Mycobacteriales Mycobacteriaceae Mycobacterium Mycobacterium tuberculosis Unknown +OAL11435.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces noursei B-3066 +OAL11436.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces noursei B-3066 +OAL11475.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces noursei B-3066 +OAQ83766.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Ophiocordycipitaceae Purpureocillium Purpureocillium lilacinum Unknown +OAQ83772.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Ophiocordycipitaceae Purpureocillium Purpureocillium lilacinum Unknown +OBR09778.1 Eukaryota Fungi Ascomycota Sordariomycetes Glomerellales Glomerellaceae Colletotrichum Colletotrichum higginsianum IMI 349063 +OJJ96433.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus aculeatus ATCC 16872 +OJJ98497.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus aculeatus ATCC 16872 +OJJ99913.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus aculeatus ATCC 16872 +OKA09423.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Amycolatopsis Amycolatopsis regifaucium GY080 +OKA09424.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Amycolatopsis Amycolatopsis regifaucium GY080 +OKA09425.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Amycolatopsis Amycolatopsis regifaucium GY080 +OKA09664.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Amycolatopsis Amycolatopsis regifaucium GY080 +OKJ61999.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. CB02009 +OLZ50885.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Amycolatopsis Amycolatopsis keratiniphila subsp. nogabecina FH 1893 +OLZ50886.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Amycolatopsis Amycolatopsis keratiniphila subsp. nogabecina FH 1893 +OLZ50899.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Amycolatopsis Amycolatopsis keratiniphila subsp. nogabecina FH 1893 +OLZ52442.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Amycolatopsis Amycolatopsis coloradensis DSM 44225 +OLZ52456.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Amycolatopsis Amycolatopsis coloradensis DSM 44225 +OLZ52457.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Amycolatopsis Amycolatopsis coloradensis DSM 44225 +ORC16617.1 Bacteria Bacillati Actinomycetota Actinomycetes Micrococcales Micrococcaceae Rothia Rothia nasimurium PT-32 +ORC16618.1 Bacteria Bacillati Actinomycetota Actinomycetes Micrococcales Micrococcaceae Rothia Rothia nasimurium PT-32 +OTA01063.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Hypocreaceae Trichoderma Trichoderma parareesei Unknown +OTA20325.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Morganellaceae Xenorhabdus Xenorhabdus beddingii DSM 4764 +P09095.2 Bacteria Bacillati Bacillota Bacilli Bacillales Paenibacillaceae Brevibacillus Brevibacillus parabrevis Unknown +P0C063.2 Bacteria Bacillati Bacillota Bacilli Bacillales Paenibacillaceae Aneurinibacillus Aneurinibacillus migulanus ATCC 9999 +P10378.3 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Enterobacteriaceae Escherichia Escherichia coli K-12 Unknown +P14687 Bacteria Bacillati Bacillota Bacilli Bacillales Paenibacillaceae Brevibacillus Brevibacillus brevis Unknown +P19828.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Vibrionales Vibrionaceae Vibrio Vibrio anguillarum Unknown +P27206.4 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus subtilis subsp. subtilis str. 168 +P39845.2 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus subtilis subsp. subtilis str. 168 +P40806.3 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus subtilis subsp. subtilis str. 168 +P40976.3 Eukaryota Fungi Ascomycota Schizosaccharomycetes Schizosaccharomycetales Schizosaccharomycetaceae Schizosaccharomyces Schizosaccharomyces pombe 972h- Unknown +P48633.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Yersiniaceae Yersinia Yersinia enterocolitica subsp. enterocolitica 8081 Unknown +P71716.2 Bacteria Bacillati Actinomycetota Actinomycetes Mycobacteriales Mycobacteriaceae Mycobacterium Mycobacterium tuberculosis H37Rv Unknown +P71717.2 Bacteria Bacillati Actinomycetota Actinomycetes Mycobacteriales Mycobacteriaceae Mycobacterium Mycobacterium tuberculosis Unknown +P94459.2 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus subtilis subsp. subtilis str. 168 +P95819 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces pristinaespiralis Unknown +PHM26612.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Morganellaceae Xenorhabdus Xenorhabdus budapestensis DSM 16342 +PHM26613.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Morganellaceae Xenorhabdus Xenorhabdus budapestensis DSM 16342 +PHM49485.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Morganellaceae Xenorhabdus Xenorhabdus miraniensis DSM 17902 +PKY04129.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus campestris IBT 28561 +PKY07881.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus campestris IBT 28561 +PLB46276.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus steynii IBT 23096 +PTB76898.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Hypocreaceae Trichoderma Trichoderma longibrachiatum ATCC 18648 +PYH50506.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus niger CBS 101883 +Q04747.3|Q45675 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus subtilis Unknown +Q0W980 Bacteria Bacillati Cyanobacteriota Cyanophyceae Oscillatoriales Microcoleaceae Planktothrix Planktothrix agardhii NIVA-CYA 126 Unknown +Q2HQW8 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Vibrionales Vibrionaceae Photobacterium Photobacterium damselae subsp. piscicida Unknown +Q4U445 Bacteria Pseudomonadati Pseudomonadota Deltaproteobacteria Myxococcales Polyangiaceae Sorangium Sorangium cellulosum Unknown +Q6E7J8 Bacteria Bacillati Cyanobacteriota Cyanophyceae Oscillatoriales Microcoleaceae Lyngbya Lyngbya majuscula Unknown +Q7BN95 Bacteria Pseudomonadati Pseudomonadota Deltaproteobacteria Myxococcales Polyangiaceae Sorangium Sorangium cellulosum Unknown +Q7D791 Bacteria Bacillati Actinomycetota Actinomycetes Mycobacteriales Mycobacteriaceae Mycobacterium Mycobacterium tuberculosis Unknown +Q7TYQ8 Bacteria Bacillati Actinomycetota Actinomycetes Mycobacteriales Mycobacteriaceae Mycobacterium Mycobacterium tuberculosis variant bovis Unknown +Q81DQ0 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus cereus ATCC 14579 Unknown +Q81QP7 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus anthracis Unknown +Q81QP9 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus anthracis Unknown +Q83M10 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Enterobacteriaceae Shigella Shigella flexneri Unknown +Q840D1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Moraxellaceae Acinetobacter Acinetobacter baumannii Unknown +Q84CG4 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces vinaceus Unknown +Q88VM6.1 Bacteria Bacillati Bacillota Bacilli Lactobacillales Lactobacillaceae Lactiplantibacillus Lactiplantibacillus plantarum WCFS1 +Q8CZT9 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Yersiniaceae Yersinia Yersinia pestis Unknown +Q8FK18 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Enterobacteriaceae Escherichia Escherichia coli O6 Unknown +Q8FK25 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Enterobacteriaceae Escherichia Escherichia coli O6 Unknown +Q8FXQ0 Bacteria Pseudomonadati Pseudomonadota Alphaproteobacteria Hyphomicrobiales Brucellaceae Brucella Brucella suis Unknown +Q8GA86 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus subtilis Unknown +Q8GAQ5 Bacteria Bacillati Cyanobacteriota Cyanophyceae Oscillatoriales Microcoleaceae Lyngbya Lyngbya majuscula Unknown +Q8K744.1 Bacteria Bacillati Bacillota Bacilli Lactobacillales Streptococcaceae Streptococcus Streptococcus pyogenes MGAS315 +Q8P0J9.1 Bacteria Bacillati Bacillota Bacilli Lactobacillales Streptococcaceae Streptococcus Streptococcus pyogenes MGAS8232 +Q8P449 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Lysobacterales Lysobacteraceae Xanthomonas Xanthomonas campestris pv. campestris Unknown +Q8PFQ6 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Lysobacterales Lysobacteraceae Xanthomonas Xanthomonas citri Unknown +Q8VM38 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces noursei Unknown +Q8VM67.2 Bacteria Bacillati Bacillota Bacilli Lactobacillales Streptococcaceae Streptococcus Streptococcus agalactiae Unknown +Q8XBV3.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Enterobacteriaceae Escherichia Escherichia coli EDL933 +Q8XBV9.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Enterobacteriaceae Escherichia Escherichia coli EDL933 +Q8Y8D4.1 Bacteria Bacillati Bacillota Bacilli Bacillales Listeriaceae Listeria Listeria monocytogenes L028 +Q8Z8L5 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Enterobacteriaceae Salmonella Salmonella enterica subsp. enterica serovar Typhi Unknown +Q8ZR32 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Enterobacteriaceae Salmonella Salmonella enterica subsp. enterica serovar Typhimurium Unknown +Q8ZR37 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Enterobacteriaceae Salmonella Salmonella enterica subsp. enterica serovar Typhimurium Unknown +Q92D47.1 Bacteria Bacillati Bacillota Bacilli Bacillales Listeriaceae Listeria Listeria innocua Clip11262 +Q93LR1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Chroococcales Microcystaceae Microcystis Microcystis aeruginosa Unknown +Q99ZA6.1 Bacteria Bacillati Bacillota Bacilli Lactobacillales Streptococcaceae Streptococcus Streptococcus pyogenes SF370 +Q9CG49.1 Bacteria Bacillati Bacillota Bacilli Lactobacillales Streptococcaceae Lactococcus Lactococcus lactis subsp. lactis IL1403 +Q9EZ79 Bacteria Pseudomonadati Pseudomonadota Alphaproteobacteria Hyphomicrobiales Brucellaceae Brucella Brucella abortus Unknown +Q9I182 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas aeruginosa Unknown +Q9K5M2 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Nostocaceae Anabaena Anabaena sp. 90 Unknown +Q9KWY7 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces viridochromogenes Unknown +Q9KWY8 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces viridochromogenes Unknown +Q9L6D0 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas fluorescens Unknown +Q9L8H4 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces anulatus Unknown +Q9RFM7 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas aeruginosa Unknown +Q9RFM8 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas aeruginosa Unknown +Q9X2N4.1 Bacteria Bacillati Bacillota Bacilli Bacillales Staphylococcaceae Staphylococcus Staphylococcus xylosus C2A +QBA57735.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. SNM55 +QBA57736.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. SNM55 +QBA57737.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. SNM55 +QBA57740.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. SNM55 +QBA57741.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. SNM55 +QBC75021.1 Bacteria None None None None None None uncultured bacterium Unknown +QBC75022.1 Bacteria None None None None None None uncultured bacterium Unknown +QBC75023.1 Bacteria None None None None None None uncultured bacterium Unknown +QBE85649.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus alliaceus FRR 5400 +QBG38782.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces atratus SCSIO Zh16 +QBG38783.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces atratus SCSIO Zh16 +QBG38784.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces atratus SCSIO Zh16 +QBK15049.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Penicillium Penicillium crustosum PRB-2 +QBQ83704.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Trichocomaceae Talaromyces Talaromyces variabilis HXQ-H-1 +QCC62990.1 Eukaryota Fungi Ascomycota Dothideomycetes Pleosporales Didymellaceae Phoma Phoma sp. F3723 +QCC62999.1 Eukaryota Fungi Ascomycota Dothideomycetes Pleosporales Didymellaceae Phoma Phoma sp. F3723 +QCE20598.1|QKW60383.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. NA03103 +QCE20608.1|QKW60392.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. NA03103 +QCE20609.1|QKW60393.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. NA03103 +QCE20614.1|QKW60398.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. NA03103 +QCP68969.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Coleofasciculales Coleofasciculaceae Moorena Moorena producens ASI16Jul14-2 +QCP68971.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Coleofasciculales Coleofasciculaceae Moorena Moorena producens ASI16Jul14-2 +QCP68975.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Coleofasciculales Coleofasciculaceae Moorena Moorena producens ASI16Jul14-2 +QCP68976.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Coleofasciculales Coleofasciculaceae Moorena Moorena producens ASI16Jul14-2 +QCQ67875.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Oscillatoriales Microcoleaceae Phormidium Phormidium sp. LP904c +QCQ67877.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Oscillatoriales Microcoleaceae Phormidium Phormidium sp. LP904c +QCQ67879.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Oscillatoriales Microcoleaceae Phormidium Phormidium sp. LP904c +QCQ67880.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Oscillatoriales Microcoleaceae Phormidium Phormidium sp. LP904c +QCQ67881.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Oscillatoriales Microcoleaceae Phormidium Phormidium sp. LP904c +QCS37521.1 Eukaryota Fungi Ascomycota Sordariomycetes Magnaporthales Pyriculariaceae Pyricularia Pyricularia grisea NI980 +QCT05750.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Kitasatospora Kitasatospora aureofaciens ATCC 31442 +QCT05762.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Kitasatospora Kitasatospora aureofaciens ATCC 31442 +QCX41944.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces novoguineensis IFO 13571; T-36496 +QCX41962.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces novoguineensis IFO 13571; T-36496 +QCY50741.1 Bacteria Bacillati Bacillota Bacilli Lactobacillales Streptococcaceae Streptococcus Streptococcus mutans 35 +QDA77045.1 Bacteria Pseudomonadati Myxococcota Polyangia Polyangiales Polyangiaceae Jahnella Jahnella sp. MSr9139 +QDA77059.1 Bacteria Pseudomonadati Myxococcota Polyangia Polyangiales Polyangiaceae Jahnella Jahnella sp. MSr9139 +QDF82254.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas sp. COR10 +QDF82255.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas sp. COR10 +QDF82259.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas sp. COR10 +QDG75033.1 Bacteria Pseudomonadati Pseudomonadota Alphaproteobacteria Hyphomicrobiales Stappiaceae Labrenzia Labrenzia sp. PHM005 +QDG75035.1 Bacteria Pseudomonadati Pseudomonadota Alphaproteobacteria Hyphomicrobiales Stappiaceae Labrenzia Labrenzia sp. PHM005 +QDJ74273.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Kitasatospora Kitasatospora sp. Unknown +QDJ74274.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Kitasatospora Kitasatospora sp. Unknown +QDJ74275.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Kitasatospora Kitasatospora sp. Unknown +QDX19369.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces hygroscopicus JCM 4712 +QED55421.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. KO-7888 +QED55422.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. KO-7888 +QED55423.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. KO-7888 +QED88054.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces hawaiiensis NRRL 15010 +QED88055.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces hawaiiensis NRRL 15010 +QEO74981.1 Bacteria None None None None None None uncultured bacterium Unknown +QEO74982.1 Bacteria None None None None None None uncultured bacterium Unknown +QEO74983.1 Bacteria None None None None None None uncultured bacterium Unknown +QEO75073.1 Bacteria None None None None None None uncultured bacterium Unknown +QEO75074.1 Bacteria None None None None None None uncultured bacterium Unknown +QEO75075.1 Bacteria None None None None None None uncultured bacterium Unknown +QEO75076.1 Bacteria None None None None None None uncultured bacterium Unknown +QEO75077.1 Bacteria None None None None None None uncultured bacterium Unknown +QGA70148.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. SNJ042 +QGR04863.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Penicillium Penicillium brasilianum WZXY-M122-9 +QHD43130.1 Eukaryota Fungi Ascomycota Sordariomycetes Sordariales Chaetomiaceae Chaetomium Chaetomium globosum E-C-2 +QIE07359.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Burkholderiaceae Burkholderia Burkholderia sp. B8(2020) B8 +QIE07362.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Burkholderiaceae Burkholderia Burkholderia sp. B8(2020) B8 +QIE07364.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Burkholderiaceae Burkholderia Burkholderia sp. B8(2020) B8 +QIH29228.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Burkholderiaceae Mycetohabitans Mycetohabitans rhizoxinica HKI454 +QIQ51365.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus nanangensis MST-FP2251 +QIW91877.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Phialomyces Phialomyces arenicola NRRL 8095 +QJA42405.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces alanosinicus ATCC 15710 +QJD55556.1 Eukaryota Fungi Basidiomycota Agaricomycetes Agaricales Physalacriaceae Strobilurus Strobilurus tenacellus Unknown +QJX57338.1 Eukaryota Fungi Ascomycota Sordariomycetes Sordariales Chaetomiaceae Chaetomium Chaetomium olivaceum SD-80A +QJY30853.1 Eukaryota Fungi Ascomycota Sordariomycetes Amphisphaeriales Sporocadaceae Discosia Discosia rubi Unknown +QKF54435.2 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. 120454 +QKF54436.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. 120454 +QKF54438.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. 120454 +QKF54440.2 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. 120454 +QKG86306.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus sp. FM242 +QKM21619.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas sp. SHC52 +QKM21620.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas sp. SHC52 +QMS79067.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus terreus var. terreus ATCC 20542 +QMW30133.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus flavus NRRL3357 +QMW33900.1|sp_B8NTZ9.1_LNAA_ASPFN Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus flavus NRRL3357 +QNH67550.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces viridosporus ATCC 14672 +QNH67551.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces viridosporus ATCC 14672 +QNH67552.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces viridosporus ATCC 14672 +QNH68024.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Penicillium Penicillium sp. PKI-1938 +QNH85840.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Burkholderiaceae Burkholderia Burkholderia gladioli HKI0521 +QNH85847.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Burkholderiaceae Burkholderia Burkholderia gladioli HKI0521 +QNL34616.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas sp. FhG100052 +QNL34617.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas sp. FhG100052 +QNL34618.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas sp. FhG100052 +QNN94286.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales None Acremonium Acremonium sp. Unknown +QOE83923.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. ID38640 +QOE83924.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. ID38640 +QOE83925.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. ID38640 +QOG08944.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus flavipes CNL-338 +QOJ72663.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Nectriaceae Xenoacremonium Xenoacremonium sp. BF-2018a ML-31 +QOW41314.1 Eukaryota Fungi Mucoromycota Mortierellomycetes Mortierellales Mortierellaceae Mortierella Mortierella alpina Unknown +QOW41315.1 Eukaryota Fungi Mucoromycota Mortierellomycetes Mortierellales Mortierellaceae Mortierella Mortierella alpina Unknown +QPC57090.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Ophiocordycipitaceae Tolypocladium Tolypocladium sp. 49Y +QPG95273.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Clavicipitaceae Epichloe Epichloe festucae Fl1 +QPG95283.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Clavicipitaceae Epichloe Epichloe festucae Fl1 +QPI18723.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Neisseriales Chromobacteriaceae Chromobacterium Chromobacterium vaccinii MWU205 +QPI18726.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Neisseriales Chromobacteriaceae Chromobacterium Chromobacterium vaccinii MWU205 +QPI18727.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Neisseriales Chromobacteriaceae Chromobacterium Chromobacterium vaccinii MWU205 +QPI18728.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Neisseriales Chromobacteriaceae Chromobacterium Chromobacterium vaccinii MWU205 +QPI18729.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Neisseriales Chromobacteriaceae Chromobacterium Chromobacterium vaccinii MWU205 +QPP19367.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Penicillium Penicillium steckii YE +QQO98485.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Hypocreaceae Cladobotryum Cladobotryum sp. Unknown +QRD90553.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus flavus NRRL 3357 +QRG35013.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. SNU533 +QRG35014.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. SNU533 +QRK05499.1 Bacteria Pseudomonadati Myxococcota Myxococcia Myxococcales Archangiaceae Archangium Archangium violaceum SDU34 +QRK05501.1 Bacteria Pseudomonadati Myxococcota Myxococcia Myxococcales Archangiaceae Archangium Archangium violaceum SDU34 +QRN75754.1 Bacteria Pseudomonadati Myxococcota Polyangia Polyangiales Sandaracinaceae Sandaracinus Sandaracinus sp. MSr10575 +QRN75755.1 Bacteria Pseudomonadati Myxococcota Polyangia Polyangiales Sandaracinaceae Sandaracinus Sandaracinus sp. MSr10575 +QTW21130.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Bionectriaceae Amphichorda Amphichorda felina SX-6-22 +QTW21132.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Bionectriaceae Amphichorda Amphichorda felina SX-6-22 +QTX15956.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus westerdijkiae Unknown +QUS58936.1 Bacteria Pseudomonadati Pseudomonadota Alphaproteobacteria Hyphomicrobiales Stappiaceae Pseudovibrio Pseudovibrio brasiliensis Ab134 +QUS58937.1 Bacteria Pseudomonadati Pseudomonadota Alphaproteobacteria Hyphomicrobiales Stappiaceae Pseudovibrio Pseudovibrio brasiliensis Ab134 +QUS58938.1 Bacteria Pseudomonadati Pseudomonadota Alphaproteobacteria Hyphomicrobiales Stappiaceae Pseudovibrio Pseudovibrio brasiliensis Ab134 +QUS58939.1 Bacteria Pseudomonadati Pseudomonadota Alphaproteobacteria Hyphomicrobiales Stappiaceae Pseudovibrio Pseudovibrio brasiliensis Ab134 +QVK45120.1 Eukaryota Fungi Ascomycota Dothideomycetes Pleosporales Didymosphaeriaceae Pseudopithomyces Pseudopithomyces chartarum Unknown +QVQ62855.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. UTZ13 +QVQ62856.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. UTZ13 +QVQ62857.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. UTZ13 +QVQ62868.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. UTZ13 +QWM97319.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Lysobacterales Lysobacteraceae Lysobacter Lysobacter sp. 3655 +QWM97320.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Lysobacterales Lysobacteraceae Lysobacter Lysobacter sp. 3655 +QWP75304.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Lysobacterales Lysobacteraceae Lysobacter Lysobacter sp. K5869 +QWP75305.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Lysobacterales Lysobacteraceae Lysobacter Lysobacter sp. K5869 +QXF14600.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales None Acremonium Acremonium sp. Unknown +QXJ21807.1 Bacteria Bacillati Actinomycetota Actinomycetes Streptosporangiales Thermomonosporaceae Actinomadura Actinomadura graeca 32-07 +QXJ21808.1 Bacteria Bacillati Actinomycetota Actinomycetes Streptosporangiales Thermomonosporaceae Actinomadura Actinomadura graeca 32-07 +QXJ21809.1 Bacteria Bacillati Actinomycetota Actinomycetes Streptosporangiales Thermomonosporaceae Actinomadura Actinomadura graeca 32-07 +QXJ26485.1 Bacteria Bacillati Actinomycetota Actinomycetes Streptosporangiales Thermomonosporaceae Actinomadura Actinomadura graeca 32-07 +QYC40287.1 Bacteria Bacillati Actinomycetota Actinomycetes Streptosporangiales Streptosporangiaceae Nonomuraea Nonomuraea coxensis DSM 45129 +QYC40288.1 Bacteria Bacillati Actinomycetota Actinomycetes Streptosporangiales Streptosporangiaceae Nonomuraea Nonomuraea coxensis DSM 45129 +QYC40289.1 Bacteria Bacillati Actinomycetota Actinomycetes Streptosporangiales Streptosporangiaceae Nonomuraea Nonomuraea coxensis DSM 45129 +QYC40290.1 Bacteria Bacillati Actinomycetota Actinomycetes Streptosporangiales Streptosporangiaceae Nonomuraea Nonomuraea coxensis DSM 45129 +QYS95804.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Hypocreaceae Trichoderma Trichoderma simmonsii GH-Sj1 +RAT94090.1 Bacteria Bacillati Bacillota Bacilli Bacillales Paenibacillaceae Brevibacillus Brevibacillus sp. Leaf182 +RAT94091.1 Bacteria Bacillati Bacillota Bacilli Bacillales Paenibacillaceae Brevibacillus Brevibacillus sp. Leaf182 +RLV71192.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. CBMAI 2042 +RLV71193.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. CBMAI 2042 +RSO11553.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. WAC 06783 +RSO11554.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. WAC 06783 +RSO11555.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. WAC 06783 +RSO11556.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. WAC 06783 +SOV25619.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Morganellaceae Xenorhabdus Xenorhabdus nematophila K102 +SOV25620.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Morganellaceae Xenorhabdus Xenorhabdus nematophila K102 +SOV25621.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Morganellaceae Xenorhabdus Xenorhabdus nematophila K102 +SOV25622.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Morganellaceae Xenorhabdus Xenorhabdus nematophila K102 +SapA Eukaryota Fungi Ascomycota Sordariomycetes Microascales Microascaceae Scedosporium Scedosporium apiosperum F41-1 +TERTU_4067 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Cellvibrionales Cellvibrionaceae Teredinibacter Teredinibacter turnerae T7901 +THA23574.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. RKND-216 +THA23575.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. RKND-216 +THA23576.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. RKND-216 +THA23581.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. RKND-216 +TRX17523.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Burkholderiaceae Trinickia Trinickia caryophylli DSM 50341 +TRX17524.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Burkholderiaceae Trinickia Trinickia caryophylli DSM 50341 +ThnA Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Hypocreaceae Trichoderma Trichoderma harzianum T22 +UEF20578.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces aurantiacus LU19075 +UEF20580.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces aurantiacus LU19075 +UEF20583.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces aurantiacus LU19075 +UEF20591.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces aurantiacus LU19075 +UEF20592.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces aurantiacus LU19075 +UHJ79948.1 Bacteria None None None None None None uncultured bacterium Unknown +UHJ79951.1 Bacteria None None None None None None uncultured bacterium Unknown +UHJ79953.1 Bacteria None None None None None None uncultured bacterium Unknown +UHY14093.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Penicillium Penicillium palitans NRRL2033 +ULE36150.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus thermomutatus Unknown +UOH28374.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus alliaceus ATCC 20738 +UWX37274.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Penicillium Penicillium oxalicum Unknown +WCD39066.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Nectriaceae Fusarium Fusarium tricinctum CGMCC 3.4731 +WCQ76523.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus carbonarius Unknown +WP_003981346.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae None Streptomyces Unknown +WP_004571777.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae None Streptomyces Unknown +WP_004571779.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae None Streptomyces Unknown +WP_004721331.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Yersiniaceae Yersinia Yersinia ruckeri Unknown +WP_004942671.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces mobaraensis Unknown +WP_004942674.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces mobaraensis Unknown +WP_004947046.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces mobaraensis Unknown +WP_004947051.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces mobaraensis Unknown +WP_006051170.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Burkholderiaceae Paraburkholderia Paraburkholderia graminis Unknown +WP_008704344.1 Bacteria Bacillati Bacillota Clostridia Eubacteriales Oscillospiraceae Ruminococcus Ruminococcus sp. 5_1_39BFAA Unknown +WP_010350604.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae None Streptomyces Unknown +WP_010350605.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae None Streptomyces Unknown +WP_010369400.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Alteromonadales Pseudoalteromonadaceae Pseudoalteromonas Pseudoalteromonas piscicida Unknown +WP_010369428.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Alteromonadales Pseudoalteromonadaceae Pseudoalteromonas Pseudoalteromonas piscicida Unknown +WP_010369430.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Alteromonadales Pseudoalteromonadaceae Pseudoalteromonas Pseudoalteromonas piscicida Unknown +WP_010639240.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. S4 Unknown +WP_010639243.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae None Streptomyces Unknown +WP_010973235.1 Bacteria Pseudomonadati Pseudomonadota Alphaproteobacteria Hyphomicrobiales Rhizobiaceae Agrobacterium Agrobacterium fabrum Unknown +WP_010973240.1 Bacteria Pseudomonadati Pseudomonadota Alphaproteobacteria Hyphomicrobiales Rhizobiaceae Agrobacterium Agrobacterium fabrum Unknown +WP_010973247.1 Bacteria Pseudomonadati Pseudomonadota Alphaproteobacteria Hyphomicrobiales Rhizobiaceae Agrobacterium Agrobacterium fabrum Unknown +WP_010973248.1 Bacteria Pseudomonadati Pseudomonadota Alphaproteobacteria Hyphomicrobiales Rhizobiaceae Agrobacterium Agrobacterium fabrum Unknown +WP_011145262.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Morganellaceae None Photorhabdus Unknown +WP_011145263.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Morganellaceae None Photorhabdus Unknown +WP_011145264.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Morganellaceae None Photorhabdus Unknown +WP_011146562.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Morganellaceae Photorhabdus Photorhabdus laumondii Unknown +WP_011146563.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Morganellaceae Photorhabdus Photorhabdus laumondii Unknown +WP_011146892.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Morganellaceae Photorhabdus Photorhabdus laumondii Unknown +WP_012118250.1 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus velezensis Unknown +WP_012408783.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Nostocaceae Nostoc Nostoc punctiforme Unknown +WP_012408785.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Nostocaceae Nostoc Nostoc punctiforme Unknown +WP_012408786.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Nostocaceae Nostoc Nostoc punctiforme Unknown +WP_013184461.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Morganellaceae Xenorhabdus Xenorhabdus nematophila Unknown +WP_013184462.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Morganellaceae Xenorhabdus Xenorhabdus nematophila Unknown +WP_013184463.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Morganellaceae Xenorhabdus Xenorhabdus nematophila Unknown +WP_013184464.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Morganellaceae Xenorhabdus Xenorhabdus nematophila Unknown +WP_013184596.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Morganellaceae Xenorhabdus Xenorhabdus nematophila Unknown +WP_013310342.1 Bacteria Bacillati Bacillota Bacilli Bacillales Paenibacillaceae Paenibacillus Paenibacillus polymyxa Unknown +WP_013310343.1 Bacteria Bacillati Bacillota Bacilli Bacillales Paenibacillaceae Paenibacillus Paenibacillus polymyxa Unknown +WP_013428324.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Burkholderiaceae Mycetohabitans Mycetohabitans rhizoxinica Unknown +WP_013428774.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Burkholderiaceae Mycetohabitans Mycetohabitans rhizoxinica Unknown +WP_014143997.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptantibioticus Streptantibioticus cattleyicolor Unknown +WP_015507661.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae None Streptomyces Unknown +WP_015507662.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae None Streptomyces Unknown +WP_015507663.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae None Streptomyces Unknown +WP_015926599.1 Bacteria Bacillati Bacillota Clostridia Eubacteriales Oscillospiraceae Ruminiclostridium Ruminiclostridium cellulolyticum Unknown +WP_016638466.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces aurantiacus Unknown +WP_016638469.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces aurantiacus Unknown +WP_016638470.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces aurantiacus Unknown +WP_016638471.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces aurantiacus Unknown +WP_018540603.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces unclassified Streptomyces Unknown +WP_018540607.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces unclassified Streptomyces Unknown +WP_019032753.1 Bacteria Bacillati Actinomycetota Actinomycetes Micromonosporales Micromonosporaceae Salinispora Salinispora arenicola Unknown +WP_019032755.1 Bacteria Bacillati Actinomycetota Actinomycetes Micromonosporales Micromonosporaceae Salinispora Salinispora arenicola Unknown +WP_019634550.1 Bacteria Bacillati Actinomycetota Actinomycetes Streptosporangiales Thermomonosporaceae Actinomadura Actinomadura atramentaria Unknown +WP_028678148.1 Bacteria Bacillati Actinomycetota Actinomycetes Micromonosporales Micromonosporaceae Salinispora Salinispora arenicola Unknown +WP_028678149.1 Bacteria Bacillati Actinomycetota Actinomycetes Micromonosporales Micromonosporaceae Salinispora Salinispora arenicola Unknown +WP_030498974.1 Bacteria Bacillati Actinomycetota Actinomycetes Micromonosporales Micromonosporaceae Micromonospora Micromonospora purpureochromogenes Unknown +WP_030498977.1 Bacteria Bacillati Actinomycetota Actinomycetes Micromonosporales Micromonosporaceae Micromonospora Micromonospora purpureochromogenes Unknown +WP_032920652.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales None None Streptomycetaceae Unknown +WP_039806850.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Azotobacter Azotobacter chroococcum Unknown +WP_039806852.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Azotobacter Azotobacter chroococcum Unknown +WP_039806856.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Azotobacter Azotobacter chroococcum Unknown +WP_041826607.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae None Streptomyces Unknown +WP_043882190.1 Bacteria Bacillati Bacillota Bacilli Bacillales Paenibacillaceae Paenibacillus Paenibacillus polymyxa Unknown +WP_044617900.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Oceanospirillales Saccharospirillaceae Gynuella Gynuella sunshinyii Unknown +WP_044618979.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Oceanospirillales Saccharospirillaceae Gynuella Gynuella sunshinyii Unknown +WP_047195042.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Sphaerotilaceae Caldimonas Caldimonas brevitalea Unknown +WP_047197778.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales None None Caldimonas brevitalea Unknown +WP_047197779.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Sphaerotilaceae Caldimonas Caldimonas brevitalea Unknown +WP_050383082.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Burkholderiaceae Burkholderia Burkholderia crenata Unknown +WP_050383084.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Burkholderiaceae Burkholderia Burkholderia crenata Unknown +WP_050383088.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Burkholderiaceae Burkholderia Burkholderia crenata Unknown +WP_050383094.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Burkholderiaceae Burkholderia Burkholderia crenata Unknown +WP_051206727.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Hapalosiphonaceae Fischerella Fischerella sp. PCC 9431 Unknown +WP_051462298.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Morganellaceae Xenorhabdus Xenorhabdus szentirmaii Unknown +WP_051700105.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. NRRL F-4474 Unknown +WP_051700122.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. NRRL F-4474 Unknown +WP_052165466.1 Bacteria Bacillati Actinomycetota Actinomycetes Micromonosporales Micromonosporaceae Micromonospora Micromonospora purpureochromogenes Unknown +WP_052830344.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Oceanospirillales Saccharospirillaceae Gynuella Gynuella sunshinyii Unknown +WP_053065269.1 Bacteria Bacillati Actinomycetota Actinomycetes Micromonosporales Micromonosporaceae Micromonospora unclassified Micromonospora Unknown +WP_053065270.1 Bacteria Bacillati Actinomycetota Actinomycetes Micromonosporales Micromonosporaceae Micromonospora unclassified Micromonospora Unknown +WP_054234617.1 Bacteria Bacillati Actinomycetota Actinomycetes None None None Actinobacteria bacterium OK006 Unknown +WP_054234643.1 Bacteria Bacillati Actinomycetota Actinomycetes None None None Actinobacteria bacterium OK006 Unknown +WP_064118559.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas fluorescens Unknown +WP_064118560.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas fluorescens Unknown +WP_064118561.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas fluorescens Unknown +WP_064118616.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas fluorescens Unknown +WP_067426775.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces lincolnensis Unknown +WP_069322367.1 Bacteria Bacillati Bacillota Bacilli Bacillales Bacillaceae Bacillus Bacillus subtilis Unknown +WP_078586793.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales None None Streptomycetaceae Unknown +WP_078587912.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces mobaraensis Unknown +WP_078620912.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces aurantiacus Unknown +WP_078857609.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae None Streptomyces Unknown +WP_078857610.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. NRRL F-4474 Unknown +WP_078857611.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. NRRL F-4474 Unknown +WP_078889006.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sclerotialus Unknown +WP_079164394.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces lincolnensis Unknown +WP_081656241.1 Bacteria Bacillati Cyanobacteriota Cyanophyceae Nostocales Hapalosiphonaceae Fischerella Fischerella sp. PCC 9431 Unknown +WP_082191961.1 Bacteria Pseudomonadati Pseudomonadota Betaproteobacteria Burkholderiales Burkholderiaceae Burkholderia Burkholderia crenata Unknown +WP_084702182.1 Bacteria Bacillati Actinomycetota Actinomycetes Pseudonocardiales Pseudonocardiaceae Amycolatopsis Amycolatopsis alba Unknown +WP_100939442.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas unclassified Pseudomonas Unknown +WP_100939443.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas unclassified Pseudomonas Unknown +WP_107406787.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces lincolnensis Unknown +WP_108867380.1 Bacteria Pseudomonadati Bacteroidota Flavobacteriia Flavobacteriales Flavobacteriaceae Aquimarina Aquimarina aquimarini Unknown +WP_108867381.1 Bacteria Pseudomonadati Bacteroidota Flavobacteriia Flavobacteriales Flavobacteriaceae Aquimarina Aquimarina aquimarini Unknown +WP_125938383.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. WAC 06738 Unknown +WP_125938384.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. WAC 06738 Unknown +WP_125939455.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. WAC 06738 Unknown +WP_125939456.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. WAC 06738 Unknown +WP_125939457.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. WAC 06738 Unknown +WP_126900392.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. WAC 01325 Unknown +WP_126900393.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. WAC 01325 Unknown +WP_126902739.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. WAC 01325 Unknown +WP_126902740.1 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. WAC 01325 Unknown +WP_129549209.1 Bacteria Bacillati Bacillota Bacilli Bacillales Paenibacillaceae Paenibacillus Paenibacillus sp. M-152 Unknown +WP_129549303.1 Bacteria Bacillati Bacillota Bacilli Bacillales Paenibacillaceae Paenibacillus Paenibacillus sp. M-152 Unknown +WP_144411596.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Pseudomonadales Pseudomonadaceae Azotobacter Azotobacter chroococcum Unknown +WP_232507913.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Enterobacterales Morganellaceae Photorhabdus Photorhabdus laumondii Unknown +WP_234859471.1 Bacteria Pseudomonadati Bacteroidota Flavobacteriia Flavobacteriales Flavobacteriaceae Aquimarina Aquimarina aquimarini Unknown +WP_234859472.1 Bacteria Pseudomonadati Bacteroidota Flavobacteriia Flavobacteriales Flavobacteriaceae Aquimarina Aquimarina aquimarini Unknown +WXC56736.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Nectriaceae Fusarium Fusarium graminearum KSU23473 +WXH65811.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Penicillium Penicillium soppii Unknown +WZI19543.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Trichocomaceae Talaromyces Talaromyces variabilis Unknown +XDO56210.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Clavicipitaceae Claviceps Claviceps purpurea Cp-1 +XDO56211.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Clavicipitaceae Claviceps Claviceps purpurea Cp-1 +XJW06604.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Penicillium Penicillium solitum HDN11-131 +XJW13335.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus parvulus Unknown +XJW13337.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus parvulus Unknown +XJW13345.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus parvulus Unknown +XPO86644.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus aculeatus Unknown +XP_001217690.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus terreus NIH2624 +XP_001258077.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus fischeri NRRL 181 +XP_002373813.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus flavus NRRL3357 +XP_002379984.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus flavus NRRL3357 +XP_003044554.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Nectriaceae Fusarium Fusarium vanettenii 77-13-4 Unknown +XP_008043822.1 Eukaryota Fungi Basidiomycota Agaricomycetes Polyporales Polyporaceae Trametes Trametes versicolor FP-101664 SS1 +XP_011325838.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Nectriaceae Fusarium Fusarium graminearum PH-1 PH-1; NRRL 31084 +XP_011387303.1 Eukaryota Fungi Basidiomycota Ustilaginomycetes Ustilaginales Ustilaginaceae Mycosarcoma Mycosarcoma maydis 521 +XP_013953110.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Hypocreaceae Trichoderma Trichoderma virens Gv29-8 +XP_020057667.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus aculeatus ATCC 16872 +XP_020058100.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus aculeatus ATCC 16872 +XP_023427367.1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Nectriaceae Fusarium Fusarium fujikuroi IMI 58289 +XP_024668732.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus candidus CBS 102.13 +XP_660225.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus nidulans FGSC A4 +XP_748654.2 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus fumigatus Af293 +XP_753088.1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus fumigatus Af293 +XP_955820.1 Eukaryota Fungi Ascomycota Sordariomycetes Sordariales Sordariaceae Neurospora Neurospora crassa OR74A +XTP71052.1 Eukaryota Fungi Ascomycota Dothideomycetes Pleosporales None None Pleosporales sp. IBWF 020-21 +YP_856987.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Aeromonadales Aeromonadaceae Aeromonas Aeromonas hydrophila subsp. hydrophila ATCC 7966 +YP_856988.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Aeromonadales Aeromonadaceae Aeromonas Aeromonas hydrophila subsp. hydrophila ATCC 7966 +YP_856990.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Aeromonadales Aeromonadaceae Aeromonas Aeromonas hydrophila subsp. hydrophila ATCC 7966 +YP_856992.1 Bacteria Pseudomonadati Pseudomonadota Gammaproteobacteria Aeromonadales Aeromonadaceae Aeromonas Aeromonas hydrophila subsp. hydrophila ATCC 7966 +antaC Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces argillaceus ATCC 12956 +antaF Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces argillaceus ATCC 12956 +astN Eukaryota Fungi Ascomycota Lecanoromycetes Ostropales Stictidaceae Cyanodermella Cyanodermella asteris Unknown +chaP_not_in_genbank Eukaryota Fungi Ascomycota Sordariomycetes Sordariales Chaetomiaceae Chaetomium Chaetomium virescens ATCC 26417 +ctg16_307 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Penicillium Penicillium citrinum JCM 22607 +ctg1_114 Eukaryota Fungi Ascomycota Dipodascomycetes Dipodascales Trichomonascaceae Wickerhamiella Wickerhamiella pararugosa NRRL Y-17089 +ctg1_116 Eukaryota Fungi Ascomycota Dipodascomycetes Dipodascales Trichomonascaceae Wickerhamiella Wickerhamiella pararugosa NRRL Y-17089 +ctg1_37 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Nectriaceae Fusarium Fusarium sp. 190-020-2 +ctg1_orf1264 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. MBT76 +ctg1_orf1265 Bacteria Bacillati Actinomycetota Actinomycetes Kitasatosporales Streptomycetaceae Streptomyces Streptomyces sp. MBT76 +ctg1_orf20 Bacteria Bacillati Actinomycetota Actinomycetes Micromonosporales Micromonosporaceae Salinispora Salinispora pacifica CNY331 +esyn1 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Nectriaceae Fusarium Fusarium proliferatum WAC11175 +g8718.t1 Eukaryota Fungi Ascomycota Sordariomycetes Coniochaetales Coniochaetaceae Coniochaeta Coniochaeta hoffmannii WAC11161 +g8724.t1 Eukaryota Fungi Ascomycota Sordariomycetes Coniochaetales Coniochaetaceae Coniochaeta Coniochaeta hoffmannii WAC11161 +g8732.t1 Eukaryota Fungi Ascomycota Sordariomycetes Coniochaetales Coniochaetaceae Coniochaeta Coniochaeta hoffmannii WAC11161 +iliA Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Nectriaceae Neonectria Neonectria sp. DH2 +osdE_fusarium_oxysporum Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Nectriaceae Fusarium Fusarium oxysporum ACCC 36465 +smbA Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Nectriaceae None Fusarium commune JCM 11502 +sp_A0A1W6BT46.1_APMB_PENBR Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Penicillium Penicillium brevicompactum Unknown +sp_A0A1W6BT53.1_APMA_PENBR Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Penicillium Penicillium brevicompactum Unknown +sp_A0A2V5H0B0.2_UNGA_ASPV1 Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus violaceofuscus CBS 115571 +sp_A1DA59.1_FTMA_NEOFI Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus fischeri NRRL 181 +sp_B8NWW5.1_LNBA_ASPFN Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus flavus NRRL3357 +sp_G3GBU7.1_BEA1_GIBIN Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Nectriaceae Fusarium Fusarium proliferatum LF061 +sp_K7NCP5.1_SIDN_EPIFI Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Clavicipitaceae Epichloe Epichloe festucae var. lolii Lp19 +sp_P9WEU8.1_BENY_ASPTE Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus terreus Unknown +sp_P9WEU9.1_BENZ_ASPTE Eukaryota Fungi Ascomycota Eurotiomycetes Eurotiales Aspergillaceae Aspergillus Aspergillus terreus Unknown +sp_W7MLD7.1_FUS1_GIBM7 Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Nectriaceae Fusarium Fusarium verticillioides 7600 +texG Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Nectriaceae Mariannaea Mariannaea elegans TTI-0396 +texJ Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Nectriaceae Mariannaea Mariannaea elegans TTI-0396 +texV Eukaryota Fungi Ascomycota Sordariomycetes Hypocreales Nectriaceae Mariannaea Mariannaea elegans TTI-0396 diff --git a/src/parasect/database/protein_identifiers.py b/src/parasect/database/protein_identifiers.py new file mode 100644 index 0000000..e69de29 From 1640795626415f67f8255e038bab74839d24071e Mon Sep 17 00:00:00 2001 From: "Terlouw, Barbara" Date: Sun, 14 Sep 2025 16:02:32 +0200 Subject: [PATCH 45/65] Add taxonomy to database --- app/src/server/parasect.db | Bin 8900608 -> 9015296 bytes src/parasect/database/build_database.py | 44 ++++++++++++- src/parasect/database/populate_database.py | 70 +++++++++++++++++++-- src/parasect/database/query_database.py | 30 ++++++++- 4 files changed, 138 insertions(+), 6 deletions(-) diff --git a/app/src/server/parasect.db b/app/src/server/parasect.db index f5a6dd38f1afa51a24f857fd43dfe68b6d58b6d4..33bbc0d83c4d1cc444d0e57ba5dcad6f52d75ada 100644 GIT binary patch delta 406151 zcmce92Vh&*bv6L*2`_m>mi1_cVHg@B9tJ^JR%8&`5-FOLEz6E$KawB`i2!H}Nt7kO zJb>EPUY6{PuC(djHfh~7ooUiENzH5?0f9KveE+#=rvfEtT z_W<#(bI(2NJNG>wcz^ACKJdZX^DFOcve_E1+pPZ@FFfMyXtJ%@f4a^2AGYR(7Mt^} z&QG^}x%J;$Hn+a7d4JRChVM1BeC*EeHJ+}o(Z-uE-DrA;z2(v;npa%h_KH;$R_-?*doy2GE{QqyqX zs#W%d3HHa0e`I{thDSGsc5Re)g$8$QH2>+PuQ#o{w7#W&rSw#2G`uA=Dh==4B@I8h zW5**>bJM8C!y&c6vkE2-CkK(~cP^|1g@s@j0JkaK# z!8t!pWdOtaxHX7hu-7|!-cl2^U;B{;?cTcm_{G~VeZB9YwV$iQukUltqqKGE)AAkX z-#Y)=`DIMX?>j&1{G{{OoF8?5*!dynk2&A#yym>%JncN{RGstIU*BL?A3pkS{DqFA zkD-)~K8SMl!eNvTExZfmss(!g-~z^KTbVn8@+~=f|3Gd%%KLK|gYCW?#%;SdJC1Ti zb`a$~S$cnW7KQCD?Rk`UYLBD5Lz7TCH59gX1w~uvPL!=37>oS}wR=!^-2X=F<9}D< zsNHkrPRF$BxbJoRLC3wXKZ

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zn7gxpLu9MgvGtkFvYT_z0SkLATPx>PfHGB5jWsdH&KmF57Vw5_Op#2s8lGK;o3T&o z84Cp{TO|ut$84EbW(Nlyp|Dr8GW;#g2$_>U{d#`FRvB}wLJlu$N*P;eUnAdh7@{d3 zvlVPp#&ixZY04_L+}xyI#R|llAy1MyZwkCCC0omTwtb0K>4vm=7!0 zBT~*Y-o{kY@T3;7n9YV?rGQzGvjH82nI`=;w%Uczq~Qy)kj;Sh8{+wWr77MZ zYd)K1R&oY&h^*E;HrZHijdCHhT3CB7`!L(Mz#+6*I68A!3jdD6ID|$EDYF^C_6=xK ze9RS5hl8?Aa`I*}&)!eai+orsJA)-~Dvxm|4Wt!fQV_2G%njLrI|+RZMX+Bed*(nKs{S9pQ2gou diff --git a/src/parasect/database/build_database.py b/src/parasect/database/build_database.py index 0f26105..b8a0461 100644 --- a/src/parasect/database/build_database.py +++ b/src/parasect/database/build_database.py @@ -1,4 +1,4 @@ -from typing import Any +from typing import Any, Optional from sys import argv from sqlalchemy import create_engine, Column, ForeignKey, Table, String, JSON @@ -31,6 +31,9 @@ class ProteinDomainAssociation(Base): protein: Mapped["Protein"] = relationship(back_populates="domains") domain: Mapped["AdenylationDomain"] = relationship(back_populates="proteins") + def __repr__(self): + return f"{self.protein.get_name()} <-> {self.domain.get_name()}" + class Substrate(Base): __tablename__ = "substrate" @@ -41,6 +44,9 @@ class Substrate(Base): domains: Mapped[list["AdenylationDomain"]] = relationship(secondary=substrate_domain_association, back_populates="substrates") + def __repr__(self): + return self.name + def to_json(self) -> dict[str, Any]: return { "name": self.name, @@ -49,16 +55,43 @@ def to_json(self) -> dict[str, Any]: } +class Taxonomy(Base): + __tablename__ = "taxonomy" + + id: Mapped[int] = mapped_column(primary_key=True) + domain: Mapped[str] + kingdom: Mapped[str] + phylum: Mapped[str] + cls: Mapped[str] + order: Mapped[str] + family: Mapped[str] + genus: Mapped[str] + species: Mapped[str] + strain: Mapped[Optional[str]] = mapped_column(nullable=True) + + proteins: Mapped[list["Protein"]] = relationship(back_populates="taxonomy") + + def __repr__(self): + return f"{self.species} {self.strain}" + + class Protein(Base): __tablename__ = "protein" id: Mapped[int] = mapped_column(primary_key=True) + + taxonomy_id: Mapped[int] = mapped_column(ForeignKey("taxonomy.id")) + taxonomy: Mapped["Taxonomy"] = relationship(back_populates="proteins") + sequence: Mapped[str] synonyms: Mapped[list["ProteinSynonym"]] = relationship(back_populates="protein") domains: Mapped[list["ProteinDomainAssociation"]] = relationship( back_populates="protein", cascade="all, delete-orphan") + def __repr__(self): + return self.get_name() + def get_name(self) -> str: """ Return the protein name @@ -77,6 +110,9 @@ class ProteinSynonym(Base): protein: Mapped[Protein] = relationship(back_populates="synonyms") + def __repr__(self): + return self.synonym + class AdenylationDomain(Base): __tablename__ = "adenylation_domain" @@ -99,6 +135,9 @@ class AdenylationDomain(Base): signature: Mapped[str] extended_signature: Mapped[str] + def __repr__(self): + return self.get_name() + def get_name(self) -> str: """ Return the domain name @@ -127,6 +166,9 @@ class DomainSynonym(Base): domain: Mapped[AdenylationDomain] = relationship(back_populates="synonyms") + def __repr__(self): + return self.synonym + def to_json(self) -> dict[str, Any]: return { "id": self.id, diff --git a/src/parasect/database/populate_database.py b/src/parasect/database/populate_database.py index 0e8e4c8..ad18c6e 100644 --- a/src/parasect/database/populate_database.py +++ b/src/parasect/database/populate_database.py @@ -7,11 +7,12 @@ from sqlalchemy.orm import Session from parasect.core.parsing import parse_fasta_file, SubstrateData, \ - parse_smiles_mapping, parse_parasect_data + parse_smiles_mapping, parse_parasect_data, TaxonomyData, parse_taxonomy_file from parasect.database.build_database import AdenylationDomain, Substrate, DomainSynonym, ProteinSynonym, Protein, \ - ProteinDomainAssociation + ProteinDomainAssociation, Taxonomy from parasect.database.query_database import sequences_are_equivalent from parasect.core.chem import smiles_to_fingerprint, is_same_molecule_fingerprint +from parasect.core.tabular import Tabular def parse_args() -> Namespace: @@ -29,11 +30,70 @@ def parse_args() -> Namespace: help="Path to fasta containing A-domain extended signatures") parser.add_argument("--protein", required=True, type=str, help="Path to fasta file containing full protein sequences") + parser.add_argument("--taxonomy", required=True, type=str, + help="Path to tab-separated file mapping proteins to taxonomy") args = parser.parse_args() return args +def create_taxonomy_entries(session: Session, protein_entries: list[Protein], taxonomy_file: str) -> None: + """Create taxonomy entries + + :param session: database session + :type session: Session + :param protein_entries: list of existing protein entries + :type protein_entries: list[Protein] + :param taxonomy_file: path to taxonomy file + :type taxonomy_file: str + """ + raw_taxonomy_mapping = parse_taxonomy_file(taxonomy_file) + taxonomy_mapping: dict[str, TaxonomyData] = {} + + for raw_key, tax_data in raw_taxonomy_mapping.items(): + # Split pipe-separated protein names + for protein_synonym in raw_key.split('|'): + taxonomy_mapping[protein_synonym] = tax_data + + existing_taxonomies = list(session.scalars(select(Taxonomy)).all()) + + # Keyed by full taxonomy + taxonomy_lookup: dict[TaxonomyData, Taxonomy] = {TaxonomyData(t.domain, t.kingdom, t.phylum, t.cls, + t.order, t.family, t.genus, t.species, + t.strain): t for t in existing_taxonomies + } + + for protein in protein_entries: + matched_tax: Optional[TaxonomyData] = None + + # Check all synonyms for a taxonomy mapping + for synonym_entry in protein.synonyms: + syn = synonym_entry.synonym + if syn in taxonomy_mapping: + matched_tax = taxonomy_mapping[syn] + break + + if matched_tax is None: + # No mapping found for any synonym; skip linking + continue + + if matched_tax in taxonomy_lookup: + taxonomy = taxonomy_lookup[matched_tax] + else: + taxonomy = Taxonomy(domain=matched_tax.domain, + kingdom=matched_tax.kingdom, + phylum=matched_tax.phylum, + cls=matched_tax.cls, + order=matched_tax.order, + family=matched_tax.family, + genus=matched_tax.genus, + species=matched_tax.species, + strain=matched_tax.strain) + taxonomy_lookup[matched_tax] = taxonomy + session.add(taxonomy) + + protein.taxonomy = taxonomy + def create_protein_entries(session: Session, protein_path: str) -> tuple[list[Protein], list[ProteinSynonym]]: """Create new protein database entries from a protein.fasta file @@ -380,10 +440,12 @@ def link_domains_and_proteins(domain_entries: list[AdenylationDomain], def populate_db(session: Session, parasect_data_path: str, smiles_path: Optional[str], signature_path: str, - extended_path: str, protein_path: str): + extended_path: str, protein_path: str, taxonomy_path: str): protein_entries, protein_synonyms = create_protein_entries(session, protein_path) + create_taxonomy_entries(session, protein_entries, taxonomy_path) + if smiles_path is not None: new_substrate_entries = create_substrate_entries(session, smiles_path) else: @@ -412,7 +474,7 @@ def main(): engine = create_engine(f"sqlite:///{args.database}") with Session(engine) as session: try: - populate_db(session, args.parasect, args.smiles, args.signature, args.extended, args.protein) + populate_db(session, args.parasect, args.smiles, args.signature, args.extended, args.protein, args.taxonomy) session.commit() except Exception as e: print(f"[ERROR] {type(e).__name__}: {e}") diff --git a/src/parasect/database/query_database.py b/src/parasect/database/query_database.py index e90c818..829ed5d 100644 --- a/src/parasect/database/query_database.py +++ b/src/parasect/database/query_database.py @@ -2,7 +2,8 @@ from sqlalchemy.orm import Session from sqlalchemy.sql import func -from parasect.database.build_database import AdenylationDomain, Substrate, DomainSynonym +from parasect.database.build_database import AdenylationDomain, Substrate, DomainSynonym, ProteinDomainAssociation, \ + ProteinSynonym, Protein from parasect.core.chem import is_same_molecule_fingerprint, smiles_to_fingerprint @@ -101,6 +102,33 @@ def get_domains_from_synonym(session: Session, synonym: str) -> list[Adenylation return list(session.scalars(query)) +def get_proteins_from_synonym(session: Session, synonym: str) -> list[Protein]: + query = select(Protein).join(ProteinSynonym).where(ProteinSynonym.synonym == synonym) + return list(session.scalars(query)) + + +def get_proteins_from_domain_synonym(session: Session, synonym: str) -> list[Protein]: + query = ( + select(Protein) + .join(Protein.domains) # Protein → ProteinDomainAssociation + .join(ProteinDomainAssociation.domain) # ProteinDomainAssociation → AdenylationDomain + .join(AdenylationDomain.synonyms) # AdenylationDomain → DomainSynonym + .where(DomainSynonym.synonym == synonym) + ) + return list(session.scalars(query).unique()) + + +def get_domains_from_protein_synonym(session: Session, synonym: str) -> list[AdenylationDomain]: + query = ( + select(AdenylationDomain) + .join(AdenylationDomain.proteins) # AdenylationDomain → ProteinDomainAssociation + .join(ProteinDomainAssociation.protein) # ProteinDomainAssociation → Protein + .join(Protein.synonyms) # Protein → ProteinSynonym + .where(ProteinSynonym.synonym == synonym) + ) + return list(session.scalars(query).unique()) + + def get_domains_from_sequence(session: Session, sequence: str) -> list[AdenylationDomain]: query = select(AdenylationDomain) domains = [] From 4b9e444e351ac79694c8ea95d7e32ba2fc29d9c1 Mon Sep 17 00:00:00 2001 From: "Terlouw, Barbara" Date: Sun, 14 Sep 2025 16:03:23 +0200 Subject: [PATCH 46/65] Add scripts for handing taxonomy --- src/parasect/core/parsing.py | 80 ++++++++++++++++++++++++++++++++++++ src/parasect/core/writers.py | 18 +++++++- 2 files changed, 97 insertions(+), 1 deletion(-) diff --git a/src/parasect/core/parsing.py b/src/parasect/core/parsing.py index 8372a89..f5a3169 100644 --- a/src/parasect/core/parsing.py +++ b/src/parasect/core/parsing.py @@ -22,6 +22,86 @@ class SubstrateData: smiles: str +@dataclass +class TaxonomyData: + domain: str + kingdom: str + phylum: str + cls: str + order: str + family: str + genus: str + species: str + strain: Optional[str] + + def __hash__(self): + + return hash((self.domain, self.kingdom, self.phylum, self.cls, self.order, self.family, self.genus, self.species, self.strain)) + +def parse_taxonomy_file(taxonomy_file: str) -> dict[str, TaxonomyData]: + """Return dictionary of protein id to taxonomy + + :param taxonomy_file: taxonomy file + :type taxonomy_file: str + :return: dict of protein to taxonomy data object + :rtype: dict[str, TaxonomyData + """ + + protein_to_taxonomy: dict[str, TaxonomyData] = {} + tax_info = Tabular(taxonomy_file, separator='\t') + for protein in tax_info.rows: + domain = tax_info.get_row_value(protein, "domain") + kingdom = tax_info.get_row_value(protein, "kingdom") + phylum = tax_info.get_row_value(protein, "phylum") + cls = tax_info.get_row_value(protein, "class") + order = tax_info.get_row_value(protein, "order") + family = tax_info.get_row_value(protein, "family") + genus = tax_info.get_row_value(protein, "genus") + species = tax_info.get_row_value(protein, "species") + strain = tax_info.get_row_value(protein, "strain") + if strain == "Unknown": + strain = None + protein_to_taxonomy[protein] = TaxonomyData(domain, kingdom, phylum, cls, order, family, genus, species, strain) + + return protein_to_taxonomy + + +def parse_raw_taxonomy(taxonomy_file: str) -> dict[str, list[str]]: + """Return dictionary of protein id to taxonomy + + :param taxonomy_file: taxonomy file + :type taxonomy_file: str + :return: dictionary of protein ID to taxonomy + :rtype: dict[str, list[str]] + """ + protein_to_taxonomy: dict[str, list[str]] = {} + with open(taxonomy_file, 'r') as tax_info: + for line in tax_info: + tax_data = line.strip().split('\t') + protein = tax_data[0] + taxonomy = tax_data[1:] + protein_to_taxonomy[protein] = taxonomy + return protein_to_taxonomy + + +def parse_list(list_file: str) -> list[str]: + """Return list of things from file containing one item per line + + :param list_file: path to file containing one string per line + :type list_file: str + :return: list of unique strings + :rtype: list[str] + """ + string_list: list[str] = [] + with open(list_file, 'r') as list_of_things: + for line in list_of_things: + line = line.strip() + if line: + string_list.append(line) + + return sorted(list(set(string_list))) + + def parse_pcs(pca_file: str) -> tuple[list[str], NDArray[np.float64]]: """Return list of domain names and numpy array of precomputed principal components for each domain diff --git a/src/parasect/core/writers.py b/src/parasect/core/writers.py index 0842fce..745cdef 100644 --- a/src/parasect/core/writers.py +++ b/src/parasect/core/writers.py @@ -46,4 +46,20 @@ def write_fasta_file(fasta_dict: dict[str, str], path_out: str) -> None: # iterate over the dictionary items for header in sorted_ids: sequence = fasta_dict[header] - fo.write(f">{header}\n{sequence}\n") \ No newline at end of file + fo.write(f">{header}\n{sequence}\n") + + +def write_list(list_of_things: list[str], out_file: str) -> None: + """Write a list of things to a file, one thing per line + + :param list_of_things: list of strings + :type list_of_things: list[str] + :param out_file: path to output file + :type out_file: str + """ + + list_of_things.sort() + + with open(out_file, 'w') as out: + for thing in list_of_things: + out.write(f"{thing}\n") From 7db57ce4eacec30a0e32e14a8eb3b54d55267c4c Mon Sep 17 00:00:00 2001 From: "Terlouw, Barbara" Date: Mon, 15 Sep 2025 10:07:51 +0200 Subject: [PATCH 47/65] Add option to train only on bacterial or fungal domains to train test splitter --- .../train_test_splits/domain_scope.py | 27 ++ .../train_test_splits/split_on_rank.py | 338 +++++++++++++----- src/parasect/core/taxonomy.py | 67 ++++ src/parasect/database/query_database.py | 17 +- 4 files changed, 357 insertions(+), 92 deletions(-) create mode 100644 model_training/data_preparation/train_test_splits/domain_scope.py create mode 100644 src/parasect/core/taxonomy.py diff --git a/model_training/data_preparation/train_test_splits/domain_scope.py b/model_training/data_preparation/train_test_splits/domain_scope.py new file mode 100644 index 0000000..d4fbdf3 --- /dev/null +++ b/model_training/data_preparation/train_test_splits/domain_scope.py @@ -0,0 +1,27 @@ +from enum import Enum + +from sqlalchemy import select + +from parasect.database.build_database import AdenylationDomain +from parasect.database.query_database import get_domains_from_taxonomic_rank +from parasect.core.taxonomy import Rank + + +class DomainScope(Enum): + BACTERIAL_ONLY = 1 + FUNGAL_ONLY = 2 + ALL = 3 + + @staticmethod + def get_domains(session, included_domains: "DomainScope"): + if included_domains == DomainScope.ALL: + domains = list(session.scalars(select(AdenylationDomain)).all()) + elif included_domains == DomainScope.FUNGAL_ONLY: + domains = get_domains_from_taxonomic_rank(session, Rank.KINGDOM, "Fungi") + elif included_domains == DomainScope.BACTERIAL_ONLY: + domains = get_domains_from_taxonomic_rank(session, Rank.DOMAIN, "Bacteria") + else: + raise ValueError(f"Unknown domain scope: {DomainScope.name}") + + return domains + \ No newline at end of file diff --git a/model_training/data_preparation/train_test_splits/split_on_rank.py b/model_training/data_preparation/train_test_splits/split_on_rank.py index b9cd7f9..a9a5670 100644 --- a/model_training/data_preparation/train_test_splits/split_on_rank.py +++ b/model_training/data_preparation/train_test_splits/split_on_rank.py @@ -5,9 +5,12 @@ from enum import Enum from sqlalchemy.orm import Session -from sqlalchemy import create_engine, select +from sqlalchemy import create_engine -from parasect.database.build_database import AdenylationDomain, Taxonomy, Substrate +from parasect.database.build_database import AdenylationDomain, Substrate +from parasect.core.taxonomy import Rank + +from .domain_scope import DomainScope def parse_arguments() -> Namespace: @@ -16,86 +19,92 @@ def parse_arguments() -> Namespace: :return: Arguments :rtype: Namespace """ - parser = ArgumentParser(description="Retrieve taxonomy for database domains") + parser = ArgumentParser(description="Split domains into train and test set based on taxonomy") parser.add_argument("-db", "--database", type=str, required=True, help="Path to PARASECT database") parser.add_argument("-o", "--output", required=True, type=str, help="Output directory") - parser.add_argument("-f", '--first_only', action="store_true", - help="If given, only consider first listed substrate for each domain.") parser.add_argument("-c", '--cutoff', default=6, type=int, help="Minimum substrate count for inclusion") parser.add_argument("-r", '--test_ratio', default=0.25, type=float, help="Target test set size") - parser.add_argument("-m", '--max_attempts', default=200, + parser.add_argument("-m", '--max_attempts', default=200, type=int, help="Max attempts made for splitting data") parser.add_argument("-t", "--taxonomic_rank", default="family", type=str, help="Taxonomic rank to split on") + mode_group = parser.add_mutually_exclusive_group() + mode_group.add_argument('--first_only', action='store_true', + help="Count only the first substrate per domain") + mode_group.add_argument('--first_valid', action='store_true', + help="Count only the first valid substrate per domain") + + domain_group = parser.add_mutually_exclusive_group() + domain_group.add_argument('--fungal_only', action='store_true', + help="Only consider fungal domains") + domain_group.add_argument('--bacterial_only', action='store_true', + help="Only consider bacterial domains") + arguments = parser.parse_args() return arguments -class SplitMode(Enum): +class SubstrateSelectionMode(Enum): FIRST_ONLY = 1 FIRST_VALID = 2 ALL = 3 @staticmethod - def get_mode_from_string(string) -> "SplitMode": - string_to_split_mode = {s.name: s for s in SplitMode} + def get_mode_from_string(string) -> Optional["SubstrateSelectionMode"]: + """ + Convert a string to a SplitMode enum value. + + :param string: String representation of split mode + :type string: str + :return: Corresponding SplitMode, or None if invalid + :rtype: SubstrateSelectionMode + """ + string_to_split_mode = {s.name: s for s in SubstrateSelectionMode} return string_to_split_mode.get(string.upper()) -class Rank(Enum): - DOMAIN = 1 - KINGDOM = 2 - PHYLUM = 3 - CLASS = 4 - ORDER = 5 - FAMILY = 6 - GENUS = 7 - SPECIES = 8 - STRAIN = 9 +def _count_first_valid_substrate(session: Session, cutoff: int, + included_domains: DomainScope = DomainScope.ALL) -> dict[Substrate, int]: + """ + Count the first valid substrate for each domain in the database, iteratively filtering + substrates that do not meet a minimum occurrence cutoff. - @staticmethod - def get_rank_from_taxonomy(rank: "Rank", taxonomy: Taxonomy) -> Optional[str]: - """ - Return specific rank from full taxonomy - :param rank: taxonomic rank - :type rank: Rank - :param taxonomy: taxonomy from database - :type taxonomy: Taxonomy - :return: string representing taxonomic rank, None if not in database - :rtype: str or None - """ - rank_to_value = {Rank.DOMAIN: taxonomy.domain, - Rank.KINGDOM: taxonomy.kingdom, - Rank.PHYLUM: taxonomy.phylum, - Rank.CLASS: taxonomy.cls, - Rank.ORDER: taxonomy.order, - Rank.FAMILY: taxonomy.family, - Rank.GENUS: taxonomy.genus, - Rank.SPECIES: taxonomy.species, - Rank.STRAIN: taxonomy.strain} - - return rank_to_value[rank] + This function performs the following steps: - @staticmethod - def get_rank_type_from_string(string: str) -> "Rank": - string_to_rank_type = {r.name: r for r in Rank} - return string_to_rank_type.get(string.upper()) + 1. Computes the total counts of all substrates across all domains, regardless of order. + 2. Identifies a set of candidate substrates that meet the specified `cutoff` globally. + 3. Iteratively assigns to each domain the first substrate (in the domain's list) that + is in the set of candidate substrates. + 4. After each iteration, any substrate whose assigned count falls below the `cutoff` + is removed from the candidate set, and the process repeats until no substrates are + pruned. + This ensures that the returned counts only include substrates that are both globally + and locally valid as "first substrates" for a sufficient number of domains. + + :param session: database session + :type session: Session + :param cutoff: minimum occurrence cutoff + :type cutoff: int + :param included_domains: determines which domains are considered (fungal, bacterial, all) + :type included_domains: DomainScope + :return: mapping of substrate to substrate counts + :rtype: dict[Substrate, int] + """ -def _count_first_valid_substrate(domains: Iterable[AdenylationDomain], cutoff: int): # Step 1: start with all substrates meeting cutoff globally + domains = DomainScope.get_domains(session, included_domains) global_counts = _count_substrates_in_domains(domains, first_only=False) valid_substrates = {s for s, c in global_counts.items() if c >= cutoff} changed = True - domain_to_valid = {} counts = {} while changed: @@ -123,13 +132,43 @@ def _count_first_valid_substrate(domains: Iterable[AdenylationDomain], cutoff: i return counts -def get_clades(session: Session, rank: Rank) -> dict[tuple[str, ...], set[AdenylationDomain]]: - """Return mapping of a group of clades of a certain rank to the domains belonging to that group +def _map_domains_to_first_valid(domains: Iterable[AdenylationDomain], + included_substrates: set[Substrate]): + """ + Assign to each domain the first substrate from `included_substrates` that appears + in its substrate list. Domains with no matching substrate are assigned None. + + :param domains: Domains to process. + :type domains: Iterable[AdenylationDomain] + :param included_substrates: Substrates considered valid for assignment. + :type included_substrates: set[Substrate] + :return: Mapping of domains to their first valid substrate or None. + :rtype: dict[AdenylationDomain, Optional[Substrate]] + """ + domain_to_first_valid = {} + + for d in domains: + for s in d.substrates: + if s in included_substrates: + domain_to_first_valid[d] = s + break + else: + # No valid substrate found + domain_to_first_valid[d] = None + + return domain_to_first_valid + + +def get_clades(session: Session, rank: Rank, + included_domains: DomainScope = DomainScope.ALL) -> dict[tuple[str, ...], set[AdenylationDomain]]: + """Group domains by clades at the specified taxonomic rank, accounting for overlapping clade memberships. :param session: database session :type session: Session :param rank: taxonomic rank :type rank: Rank + :param included_domains: determines which domains are considered (fungal, bacterial, all) + :type included_domains: DomainScope :return: dictionary mapping clade groups (e.g. (Burkholderiaceae, Pseudomonadaceae) to domains :rtype: dict[tuple[str, ...], set[AdenylationDomain]] """ @@ -137,7 +176,7 @@ def get_clades(session: Session, rank: Rank) -> dict[tuple[str, ...], set[Adenyl # belong to different taxonomic lineages. E.g., domain ADH01485.1.A1|AIC32693.1.A1 belongs to both the # Burkholderiaceae (ADH01485.1.A1) and the Pseudomonadaceae (AIC32693.1.A1) families - domains = list(session.scalars(select(AdenylationDomain)).all()) + domains = DomainScope.get_domains(session, included_domains) clade_to_domains: dict[str, set[AdenylationDomain]] = {} clade_to_clade_group: dict[str, set[str]] = {} for domain in domains: @@ -170,7 +209,7 @@ def get_clades(session: Session, rank: Rank) -> dict[tuple[str, ...], set[Adenyl def _count_substrates_in_domains(domains: Iterable[AdenylationDomain], first_only: bool) -> dict[Substrate, int]: - """Count substrate specificities of domains + """Count substrates in a collection of domains. :param domains: collection of unique adenylation domains :type domains: Iterable[AdenylationDomain] @@ -193,8 +232,9 @@ def _count_substrates_in_domains(domains: Iterable[AdenylationDomain], return counts -def count_substrates(session: Session, first_only: bool, cutoff: int = 0) -> dict[Substrate, int]: - """Count substrate occurrences in database +def count_substrates(session: Session, first_only: bool, cutoff: int = 0, + included_domains: DomainScope = DomainScope.ALL) -> dict[Substrate, int]: + """Count occurrences of substrates across all domains, optionally filtering by cutoff. :param session: database session :type session: Session @@ -202,10 +242,13 @@ def count_substrates(session: Session, first_only: bool, cutoff: int = 0) -> dic :type first_only: bool :param cutoff: only include substrates that occur at least this many times :type cutoff: int + :param included_domains: determines which domains are considered (fungal, bacterial, all) + :type included_domains: DomainScope :return: dictionary mapping substrate to substrate counts :rtype: dict[Substrate, int] """ - domains = list(session.scalars(select(AdenylationDomain)).all()) + domains = DomainScope.get_domains(session, included_domains) + substrate_to_count = _count_substrates_in_domains(domains, first_only) for substrate, count in list(substrate_to_count.items()): @@ -215,10 +258,33 @@ def count_substrates(session: Session, first_only: bool, cutoff: int = 0) -> dic return substrate_to_count +def get_counts_per_clade_first_valid(clade_group_to_domains: dict[tuple[str, ...], set[AdenylationDomain]], + included_substrates: set[Substrate]) -> dict[tuple[str, ...], dict[Substrate, int]]: + """ + Count first valid substrates for each clade group. + + :param clade_group_to_domains: Mapping of clade tuples → domains + :type clade_group_to_domains: dict[tuple[str, ...], set[AdenylationDomain]] + :param included_substrates: Substrates considered valid + :type included_substrates: set[Substrate] + :return: Mapping of clade tuples → substrate counts + :rtype: dict[tuple[str, ...], dict[Substrate, int]] + """ + counts_per_clade = {} + for clade, domains in clade_group_to_domains.items(): + domain_to_valid = _map_domains_to_first_valid(domains, included_substrates) + substrate_counts = {s: 0 for s in included_substrates} + for s in domain_to_valid.values(): + if s is not None: + substrate_counts[s] += 1 + counts_per_clade[clade] = substrate_counts + return counts_per_clade + + def get_counts_per_clade(clade_group_to_domains: dict[tuple[str, ...], set[AdenylationDomain]], included_substrates: set[Substrate], first_only: bool) -> dict[tuple[str, ...], dict[Substrate, int]]: - """Return dictionary recording substrate counts for each clade + """Count substrates for each clade group, optionally only counting first substrates. :param clade_group_to_domains: dictionary mapping clade groups to domains :type clade_group_to_domains: dict[tuple[str, ...], set[AdenylationDomain]] @@ -242,13 +308,37 @@ def get_counts_per_clade(clade_group_to_domains: dict[tuple[str, ...], set[Adeny return counts_per_clade +def check_split_possible(clade_substrate_counts: dict[tuple[str, ...], dict], substrates: set[Substrate]) -> bool: + """ + Check if all substrates appear in at least two clades, required for splitting train/test sets. + + :param clade_substrate_counts: dict mapping clade groups → substrate counts + :type clade_substrate_counts: dict[tuple[str, ...], dict] + :param substrates: set of substrates to check + :type substrates: set[Substrate] + :return: True if split possible, False otherwise + """ + for sub in substrates: + clades_with_sub = [clade for clade, counts in clade_substrate_counts.items() if counts.get(sub, 0) > 0] + if len(clades_with_sub) < 2: + print(f"Substrate {sub} occurs in less than 2 clades: {len(clades_with_sub)}") + return False + return True + + def split_on_rank(session: Session, rank: Rank, cutoff: int = 6, target_ratio: float = 0.75, - first_only: bool = True, + split_mode: SubstrateSelectionMode = SubstrateSelectionMode.FIRST_ONLY, + included_domains: DomainScope = DomainScope.ALL, max_attempts: int = 200) -> dict[str, dict]: - """Split dataset into phylogenetically distinct train and test set based on taxonomic rank + """Split domains into train/test sets based on taxonomic rank while balancing substrate representation. + + Ensures: + - Each substrate occurs in both train and test sets + - Domains from the same clade are assigned to the same set + - Substrate counts are as balanced as possible according to target_ratio :param session: database session :type session: Session @@ -259,19 +349,39 @@ def split_on_rank(session: Session, :type cutoff: int :param target_ratio: target ratio of datapoints in training set :type target_ratio: float - :param first_only: if True, consider only the first listed subsrate for each domain. Default: True - :type first_only: bool + :param split_mode: determines which substrates are considered for splitting the data + :type split_mode: SplitMode + :param included_domains: determines which domains are considered (fungal, bacterial, all) + :type split_mode: DomainScope :param max_attempts: maximum number of attempts to try splitting the dataset. Default: 200 :type max_attempts: int :return: dictionary containing clade mappings (assignment) and substrate counts :rtype: dict[str, dict] """ rng = random.Random(100125) - substrate_to_count = count_substrates(session, first_only, cutoff) + # Decide included substrates based on mode + if split_mode == SubstrateSelectionMode.ALL: + substrate_to_count = count_substrates(session, first_only=False, cutoff=cutoff, + included_domains=included_domains) + elif split_mode == SubstrateSelectionMode.FIRST_ONLY: + substrate_to_count = count_substrates(session, first_only=True, cutoff=cutoff, + included_domains=included_domains) + elif split_mode == SubstrateSelectionMode.FIRST_VALID: + + substrate_to_count = _count_first_valid_substrate(session, cutoff, included_domains=included_domains) + else: + raise ValueError(f"Unknown split mode: {split_mode}") + substrates = list(substrate_to_count.keys()) substrates.sort(key=lambda x: x.name) - grouped_clades = get_clades(session, rank) - clade_substrate_counts = get_counts_per_clade(grouped_clades, set(substrate_to_count.keys()), first_only) + + grouped_clades = get_clades(session, rank, included_domains=included_domains) + + if split_mode == SubstrateSelectionMode.FIRST_VALID: + clade_substrate_counts = get_counts_per_clade_first_valid(grouped_clades, set(substrates)) + else: + clade_substrate_counts = get_counts_per_clade(grouped_clades, set(substrate_to_count.keys()), + first_only=(split_mode == SubstrateSelectionMode.FIRST_ONLY)) # coverage phase: ensure each substrate occurs in both train and test set def try_build_coverage(): @@ -306,6 +416,7 @@ def try_build_coverage(): return assignment coverage_assignment = None + for _ in range(max_attempts): coverage_assignment = try_build_coverage() if coverage_assignment: @@ -355,16 +466,20 @@ def total_error(counts): for clade, side in coverage_assignment.items(): for domain in grouped_clades[clade]: if domain in domain_assignment: - raise RuntimeError( - f"Domain {domain} assigned twice " - f"({domain_assignment[domain]} and {side})" - ) - if first_only: - if domain.substrates[0] in substrates: - domain_assignment[domain] = side - else: + raise RuntimeError(f"Domain {domain} assigned twice") + + if split_mode == SubstrateSelectionMode.ALL: if any(sub in substrates for sub in domain.substrates): domain_assignment[domain] = side + elif split_mode == SubstrateSelectionMode.FIRST_ONLY: + if domain.substrates[0] in substrates: + domain_assignment[domain] = side + elif split_mode == SubstrateSelectionMode.FIRST_VALID: + # assign based on first valid substrate + for s in domain.substrates: + if s in substrates: + domain_assignment[domain] = side + break return { "assignment": coverage_assignment, @@ -375,6 +490,21 @@ def total_error(counts): def main(): args = parse_arguments() + + if args.first_only: + split_mode = SubstrateSelectionMode.FIRST_ONLY + elif args.first_valid: + split_mode = SubstrateSelectionMode.FIRST_VALID + else: + split_mode = SubstrateSelectionMode.ALL + + if args.fungal_only: + included_domains = DomainScope.FUNGAL_ONLY + elif args.bacterial_only: + included_domains = DomainScope.BACTERIAL_ONLY + else: + included_domains = DomainScope.ALL + engine = create_engine(f"sqlite:///{args.database}") if not os.path.exists(args.output): os.mkdir(args.output) @@ -392,7 +522,8 @@ def main(): result = split_on_rank(session, rank_type, cutoff=args.cutoff, target_ratio=1.0 - args.test_ratio, - first_only=args.first_only, + split_mode=split_mode, + included_domains=included_domains, max_attempts=args.max_attempts) clade_assignment = result["assignment"] @@ -456,7 +587,7 @@ def main(): f"Sanity check failed: test substrate count ({total_test}) " f"!= number of test domains ({num_test_domains})." ) - else: + elif not args.first_valid: # 1. No domain assigned twice assigned_domains = set() for domain, side in domain_assignment.items(): @@ -484,7 +615,7 @@ def main(): # Get all domains that have at least one substrate in the counted list legal_domains = set() - for domain in session.scalars(select(AdenylationDomain)).all(): + for domain in DomainScope.get_domains(session, included_domains): if any(sub in substrate_counts for sub in domain.substrates): legal_domains.add(domain) @@ -501,24 +632,49 @@ def main(): f"{len(extra)} extra domains assigned" ) - test_substrates = set() - train_substrates = set() - for domain, assignment in domain_assignment.items(): - first_valid_substrate = None - for substrate in domain.substrates: - if substrate in substrate_counts: - first_valid_substrate = substrate - break - assert first_valid_substrate is not None - if assignment == 'test': - test_substrates.add(first_valid_substrate) - elif assignment == 'train': - train_substrates.add(first_valid_substrate) - - if train_substrates != test_substrates: - for substrate in train_substrates ^ test_substrates: - print(substrate_counts[substrate]) - print(train_substrates - test_substrates) + else: + assigned_domains = set() + + # 1. Ensure no domain assigned twice + for domain, side in domain_assignment.items(): + if domain in assigned_domains: + raise RuntimeError(f"Domain {domain} assigned twice") + assigned_domains.add(domain) + + # 2. Verify counted substrates match assigned domains + for sub, counts in substrate_counts.items(): + counted_train = sum(1 for d, side in domain_assignment.items() + if + side == "train" and sub == next((s for s in d.substrates if s in substrate_counts), + None)) + counted_test = sum(1 for d, side in domain_assignment.items() + if side == "test" and sub == next((s for s in d.substrates if s in substrate_counts), + None)) + + if counted_train != counts["train"]: + raise RuntimeError( + f"Mismatch for substrate {sub}: train counted {counts['train']}, sum over domains {counted_train}" + ) + if counted_test != counts["test"]: + raise RuntimeError( + f"Mismatch for substrate {sub}: test counted {counts['test']}, sum over domains {counted_test}" + ) + + # 3. Ensure all domains with at least one valid substrate are assigned + legal_domains = set() + for domain in DomainScope.get_domains(session, included_domains): + if any(sub in substrate_counts for sub in domain.substrates): + legal_domains.add(domain) + + missing = legal_domains - assigned_domains + extra = assigned_domains - legal_domains + + if missing or extra: + raise RuntimeError( + f"Domain assignment mismatch: " + f"{len(missing)} legal domains missing, " + f"{len(extra)} extra domains assigned" + ) if __name__ == "__main__": diff --git a/src/parasect/core/taxonomy.py b/src/parasect/core/taxonomy.py new file mode 100644 index 0000000..bc9dff5 --- /dev/null +++ b/src/parasect/core/taxonomy.py @@ -0,0 +1,67 @@ +from typing import Optional +from enum import Enum + +from parasect.database.build_database import Taxonomy + + +class Rank(Enum): + DOMAIN = 1 + KINGDOM = 2 + PHYLUM = 3 + CLASS = 4 + ORDER = 5 + FAMILY = 6 + GENUS = 7 + SPECIES = 8 + STRAIN = 9 + + @staticmethod + def get_column(rank: "Rank"): + rank_to_column = { + Rank.DOMAIN: Taxonomy.domain, + Rank.KINGDOM: Taxonomy.kingdom, + Rank.PHYLUM: Taxonomy.phylum, + Rank.CLASS: Taxonomy.cls, + Rank.ORDER: Taxonomy.order, + Rank.FAMILY: Taxonomy.family, + Rank.GENUS: Taxonomy.genus, + Rank.SPECIES: Taxonomy.species, + Rank.STRAIN: Taxonomy.strain, + } + return rank_to_column[rank] + + @staticmethod + def get_rank_from_taxonomy(rank: "Rank", taxonomy: Taxonomy) -> Optional[str]: + """ + Return specific rank from full taxonomy + :param rank: taxonomic rank + :type rank: Rank + :param taxonomy: taxonomy from database + :type taxonomy: Taxonomy + :return: string representing taxonomic rank, None if not in database + :rtype: str or None + """ + rank_to_value = {Rank.DOMAIN: taxonomy.domain, + Rank.KINGDOM: taxonomy.kingdom, + Rank.PHYLUM: taxonomy.phylum, + Rank.CLASS: taxonomy.cls, + Rank.ORDER: taxonomy.order, + Rank.FAMILY: taxonomy.family, + Rank.GENUS: taxonomy.genus, + Rank.SPECIES: taxonomy.species, + Rank.STRAIN: taxonomy.strain} + + return rank_to_value[rank] + + @staticmethod + def get_rank_type_from_string(string: str) -> Optional["Rank"]: + """ + Convert a string to a Rank enum value. + + :param string: Taxonomic rank name (case-insensitive) + :type string: str + :return: Corresponding Rank, or None if invalid + :rtype: Optional[Rank] + """ + string_to_rank_type = {r.name: r for r in Rank} + return string_to_rank_type.get(string.upper()) diff --git a/src/parasect/database/query_database.py b/src/parasect/database/query_database.py index 829ed5d..2e90b52 100644 --- a/src/parasect/database/query_database.py +++ b/src/parasect/database/query_database.py @@ -3,8 +3,9 @@ from sqlalchemy.sql import func from parasect.database.build_database import AdenylationDomain, Substrate, DomainSynonym, ProteinDomainAssociation, \ - ProteinSynonym, Protein + ProteinSynonym, Protein, Taxonomy from parasect.core.chem import is_same_molecule_fingerprint, smiles_to_fingerprint +from parasect.core.taxonomy import Rank def get_protein_names(session: Session): @@ -92,6 +93,20 @@ def get_substrates_from_smiles(session: Session, smiles: str) -> list[Substrate] return substrates +def get_domains_from_taxonomic_rank(session: Session, rank: Rank, rank_name: str) -> list[AdenylationDomain]: + + taxonomy_column = Rank.get_column(rank) + query = ( + select(AdenylationDomain) + .join(AdenylationDomain.proteins) + .join(ProteinDomainAssociation.protein) + .join(Protein.taxonomy) + .where(taxonomy_column == rank_name) + .distinct() + ) + return list(session.scalars(query).all()) + + def get_substrates_from_name(session: Session, substrate_name: str) -> list[Substrate]: query = select(Substrate).where(func.lower(Substrate.name) == substrate_name.lower()) return list(session.scalars(query)) From cdf5ebdcdb8f01610d286fc7993f949747796fba Mon Sep 17 00:00:00 2001 From: "Terlouw, Barbara" Date: Mon, 15 Sep 2025 16:02:28 +0200 Subject: [PATCH 48/65] Finalise train test splitters --- model_training/rf/train_rf.py | 50 ---- src/parasect/database/build_database.py | 13 + src/parasect/database/query_database.py | 14 ++ .../data_preparation/__init__.py | 0 .../data_preparation/taxonomy/__init__.py | 0 .../parasect/model_training/pca}/__init__.py | 0 .../parasect/model_training}/pca/apply_pca.py | 0 .../parasect/model_training}/pca/build_pca.py | 0 .../parasect/model_training/rf}/__init__.py | 0 src/parasect/model_training/rf/train_rf.py | 94 ++++++++ .../train_test_splits}/__init__.py | 0 .../train_test_splits/crossvalidation.py | 45 ++++ .../train_test_splits/domain_scope.py | 0 .../multilabel_stratification.py | 7 + .../train_test_splits/split_on_rank.py | 226 ++++-------------- .../train_test_splits/split_on_substrate.py | 192 +++++++++++++++ .../train_test_splits/substrate_selection.py | 186 ++++++++++++++ 17 files changed, 594 insertions(+), 233 deletions(-) delete mode 100644 model_training/rf/train_rf.py rename {model_training => src/parasect/model_training}/data_preparation/__init__.py (100%) rename {model_training => src/parasect/model_training}/data_preparation/taxonomy/__init__.py (100%) rename {model_training/data_preparation/train_test_splits => src/parasect/model_training/pca}/__init__.py (100%) rename {model_training => src/parasect/model_training}/pca/apply_pca.py (100%) rename {model_training => src/parasect/model_training}/pca/build_pca.py (100%) rename {model_training/pca => src/parasect/model_training/rf}/__init__.py (100%) create mode 100644 src/parasect/model_training/rf/train_rf.py rename {model_training/rf => src/parasect/model_training/train_test_splits}/__init__.py (100%) create mode 100644 src/parasect/model_training/train_test_splits/crossvalidation.py rename {model_training/data_preparation => src/parasect/model_training}/train_test_splits/domain_scope.py (100%) create mode 100644 src/parasect/model_training/train_test_splits/multilabel_stratification.py rename {model_training/data_preparation => src/parasect/model_training}/train_test_splits/split_on_rank.py (75%) create mode 100644 src/parasect/model_training/train_test_splits/split_on_substrate.py create mode 100644 src/parasect/model_training/train_test_splits/substrate_selection.py diff --git a/model_training/rf/train_rf.py b/model_training/rf/train_rf.py deleted file mode 100644 index cf5ce89..0000000 --- a/model_training/rf/train_rf.py +++ /dev/null @@ -1,50 +0,0 @@ -from typing import Optional - -from joblib import dump -from numpy.typing import NDArray -import numpy as np -from sklearn.ensemble import RandomForestClassifier - -from parasect.core.parsing import parse_pcs, parse_fasta_file, parse_parasect_data -from parasect.core.featurisation import get_domain_features - - -def train_random_forest(features: NDArray[np.float64], labels: list[str], out_path: Optional[str] = None) -> None: - """ - - :param features: feature matrix - :type features: NDArray[np.float64] - :param labels: prediction labels - :type labels: list[str] - :param out_path: If given store model to specified output path - :type out_path: Optional[str] - """ - model = RandomForestClassifier( - n_estimators=1000, - n_jobs=1, - oob_score=True, - random_state=25051989, - class_weight="balanced", - ) - - model.fit(features, labels, sample_weight="balanced") - if out_path is not None: - dump(model, out_path) - - -def train_rf_esm_pca(): - pass - - -def train_rf_signatures(signatures_fasta: str, domain_to_substrate_mapping: str, out_file: str) -> None: - """Train RF on amino acid signatures - - :param signatures_fasta: path to fasta file containing amino acid signatures - :type signatures_fasta: str - :param domain_to_substrate_mapping: path to file containing domain to substrate mapping - :type domain_to_substrate_mapping: str - :param out_file: path to model output file - :type out_file: str - """ - pass - diff --git a/src/parasect/database/build_database.py b/src/parasect/database/build_database.py index b8a0461..37c86c7 100644 --- a/src/parasect/database/build_database.py +++ b/src/parasect/database/build_database.py @@ -47,6 +47,19 @@ class Substrate(Base): def __repr__(self): return self.name + def __eq__(self, other): + if not isinstance(other, Substrate): + return NotImplemented + return self.name == other.name + + def __hash__(self): + return hash(self.name) + + def __lt__(self, other): + if not isinstance(other, Substrate): + return NotImplemented + return self.name < other.name + def to_json(self) -> dict[str, Any]: return { "name": self.name, diff --git a/src/parasect/database/query_database.py b/src/parasect/database/query_database.py index 2e90b52..71c89c9 100644 --- a/src/parasect/database/query_database.py +++ b/src/parasect/database/query_database.py @@ -117,6 +117,20 @@ def get_domains_from_synonym(session: Session, synonym: str) -> list[Adenylation return list(session.scalars(query)) +def get_domains_from_names(session: Session, names: list[str]) -> list[AdenylationDomain]: + if not names: + return [] + + query = ( + select(AdenylationDomain) + .join(DomainSynonym) + .where(DomainSynonym.synonym.in_(names)) + .distinct() # <-- ensures unique AdenylationDomain rows + ) + + return list(session.scalars(query)) + + def get_proteins_from_synonym(session: Session, synonym: str) -> list[Protein]: query = select(Protein).join(ProteinSynonym).where(ProteinSynonym.synonym == synonym) return list(session.scalars(query)) diff --git a/model_training/data_preparation/__init__.py b/src/parasect/model_training/data_preparation/__init__.py similarity index 100% rename from model_training/data_preparation/__init__.py rename to src/parasect/model_training/data_preparation/__init__.py diff --git a/model_training/data_preparation/taxonomy/__init__.py b/src/parasect/model_training/data_preparation/taxonomy/__init__.py similarity index 100% rename from model_training/data_preparation/taxonomy/__init__.py rename to src/parasect/model_training/data_preparation/taxonomy/__init__.py diff --git a/model_training/data_preparation/train_test_splits/__init__.py b/src/parasect/model_training/pca/__init__.py similarity index 100% rename from model_training/data_preparation/train_test_splits/__init__.py rename to src/parasect/model_training/pca/__init__.py diff --git a/model_training/pca/apply_pca.py b/src/parasect/model_training/pca/apply_pca.py similarity index 100% rename from model_training/pca/apply_pca.py rename to src/parasect/model_training/pca/apply_pca.py diff --git a/model_training/pca/build_pca.py b/src/parasect/model_training/pca/build_pca.py similarity index 100% rename from model_training/pca/build_pca.py rename to src/parasect/model_training/pca/build_pca.py diff --git a/model_training/pca/__init__.py b/src/parasect/model_training/rf/__init__.py similarity index 100% rename from model_training/pca/__init__.py rename to src/parasect/model_training/rf/__init__.py diff --git a/src/parasect/model_training/rf/train_rf.py b/src/parasect/model_training/rf/train_rf.py new file mode 100644 index 0000000..4dca317 --- /dev/null +++ b/src/parasect/model_training/rf/train_rf.py @@ -0,0 +1,94 @@ +from typing import Optional + +from joblib import dump +from numpy.typing import NDArray +import numpy as np +from sklearn.ensemble import RandomForestClassifier +from sqlalchemy.orm import Session + +from parasect.core.featurisation import get_domain_features +from parasect.database.query_database import get_domains_from_names, get_substrates_from_name +from parasect.core.parsing import parse_list +from parasect.model_training.train_test_splits.substrate_selection import SubstrateSelectionMode, \ + map_domains_to_substrates + + +def train_random_forest(features: NDArray[np.float64], labels: NDArray[np.str], + out_path: Optional[str] = None) -> RandomForestClassifier: + """ + + :param features: feature matrix + :type features: NDArray[np.float64] + :param labels: prediction labels + :type labels: list[str] + :param out_path: If given store model to specified output path + :type out_path: Optional[str] + """ + model = RandomForestClassifier( + n_estimators=1000, + n_jobs=1, + oob_score=True, + random_state=25051989, + class_weight="balanced", + ) + + model.fit(features, labels, sample_weight="balanced") + if out_path is not None: + dump(model, out_path) + + return model + + +def train_rf_esm_pca(): + pass + + +def train_paras_signatures(session: Session, domain_list: str, + selection_mode: SubstrateSelectionMode, + included_substrates_file: str, + out_path: Optional[str] = None) -> RandomForestClassifier: + """ + + :param session: database session + :type session: Session + :param selection_mode: determines which substrates are considered + :type selection_mode: SubstrateSelectionMode + :param included_substrates_file: path to file containing included substrates + :type included_substrates_file: str + :param domain_list: file path containing list of domains to train on + :type domain_list: str + :param out_path: if given, save model to out path + :type out_path: Optional[str + + """ + + if selection_mode not in [SubstrateSelectionMode.FIRST_VALID, SubstrateSelectionMode.FIRST_ONLY]: + raise ValueError(f"Unsupported substrate selection mode for training PARAS: {selection_mode.name}") + + domain_names = parse_list(domain_list) + + domains = get_domains_from_names(session, domain_names) + + domains.sort(key=lambda x: x.get_name()) + included_substrate_names = parse_list(included_substrates_file) + included_substrates = set() + for name in included_substrate_names: + included_substrates.add(get_substrates_from_name(session, name)[0]) + + domain_to_substrate = map_domains_to_substrates(domains, included_substrates, selection_mode=selection_mode) + + features = np.array([get_domain_features(domain.extended_signature) for domain in domains]) + labels = np.array([domain_to_substrate[domain].name for domain in domains]) + + classifier = train_random_forest(features, labels, out_path=out_path) + + return classifier + + + + + + + + + diff --git a/model_training/rf/__init__.py b/src/parasect/model_training/train_test_splits/__init__.py similarity index 100% rename from model_training/rf/__init__.py rename to src/parasect/model_training/train_test_splits/__init__.py diff --git a/src/parasect/model_training/train_test_splits/crossvalidation.py b/src/parasect/model_training/train_test_splits/crossvalidation.py new file mode 100644 index 0000000..a20b7c9 --- /dev/null +++ b/src/parasect/model_training/train_test_splits/crossvalidation.py @@ -0,0 +1,45 @@ +import os +from collections import Counter +from typing import Optional, Union + +from sklearn.model_selection import StratifiedKFold +from iterstrat.ml_stratifiers import MultilabelStratifiedKFold + +from parasect.database.build_database import AdenylationDomain, Substrate +from parasect.core.writers import write_list +from parasect.model_training.train_test_splits.substrate_selection import SubstrateSelectionMode + + +def make_crossval_sets(train_x: list[AdenylationDomain], train_y: Union[list[Substrate], list[list[Substrate]]], + out_dir: str, + fold_validation: int = 3, binary_labels: Optional[list] = None, + selection_mode: SubstrateSelectionMode = SubstrateSelectionMode.FIRST_ONLY) -> None: + if selection_mode != SubstrateSelectionMode.ALL: + stratifier = StratifiedKFold(n_splits=fold_validation, random_state=25051989, shuffle=True) + splits = stratifier.split(train_x, [s.name for s in train_y]) + else: + stratifier = MultilabelStratifiedKFold(n_splits=fold_validation, random_state=25051989, shuffle=True) + splits = stratifier.split(train_x, binary_labels) + + for i, (train_indices, test_indices) in enumerate(splits): + out_train = os.path.join(out_dir, f"train_crossvalidation_{i + 1}.txt") + out_test = os.path.join(out_dir, f"test_crossvalidation_{i + 1}.txt") + counts_out = os.path.join(out_dir, f"crossvalidation_substrate_counts_{i + 1}.txt") + + train = [train_x[j].get_name() for j in train_indices] + test = [train_x[j].get_name() for j in test_indices] + + if selection_mode != SubstrateSelectionMode.ALL: + substrates_train = Counter([train_y[j].name for j in train_indices]) + substrates_test = Counter([train_y[j].name for j in test_indices]) + else: + substrates_train = Counter([substrate.name for j in train_indices for substrate in train_y[j]]) + substrates_test = Counter([substrate.name for j in test_indices for substrate in train_y[j]]) + + with open(counts_out, 'w') as out: + out.write(f"substrate\ttrain\ttest\n") + for substrate in sorted(set(substrates_train) | set(substrates_test)): + out.write(f"{substrate}\t{substrates_train[substrate]}\t{substrates_test[substrate]}\n") + + write_list(train, out_train) + write_list(test, out_test) diff --git a/model_training/data_preparation/train_test_splits/domain_scope.py b/src/parasect/model_training/train_test_splits/domain_scope.py similarity index 100% rename from model_training/data_preparation/train_test_splits/domain_scope.py rename to src/parasect/model_training/train_test_splits/domain_scope.py diff --git a/src/parasect/model_training/train_test_splits/multilabel_stratification.py b/src/parasect/model_training/train_test_splits/multilabel_stratification.py new file mode 100644 index 0000000..65c6118 --- /dev/null +++ b/src/parasect/model_training/train_test_splits/multilabel_stratification.py @@ -0,0 +1,7 @@ +import numpy as np +from sklearn.preprocessing import MultiLabelBinarizer + +def binarise_data(labels: list[list[str]]) -> tuple[np.ndarray, np.ndarray]: + mlb = MultiLabelBinarizer() + new_labels = mlb.fit_transform(labels) + return new_labels, mlb.classes_ \ No newline at end of file diff --git a/model_training/data_preparation/train_test_splits/split_on_rank.py b/src/parasect/model_training/train_test_splits/split_on_rank.py similarity index 75% rename from model_training/data_preparation/train_test_splits/split_on_rank.py rename to src/parasect/model_training/train_test_splits/split_on_rank.py index a9a5670..77cd12a 100644 --- a/model_training/data_preparation/train_test_splits/split_on_rank.py +++ b/src/parasect/model_training/train_test_splits/split_on_rank.py @@ -1,8 +1,7 @@ import random import os -from typing import Optional, Iterable + from argparse import ArgumentParser, Namespace -from enum import Enum from sqlalchemy.orm import Session from sqlalchemy import create_engine @@ -10,7 +9,12 @@ from parasect.database.build_database import AdenylationDomain, Substrate from parasect.core.taxonomy import Rank -from .domain_scope import DomainScope +from parasect.model_training.train_test_splits.domain_scope import DomainScope +from parasect.model_training.train_test_splits.substrate_selection import SubstrateSelectionMode, \ + count_first_valid_substrate, map_domains_to_substrates, count_substrates_in_domains, count_substrates +from parasect.model_training.train_test_splits.multilabel_stratification import binarise_data +from parasect.model_training.train_test_splits.crossvalidation import make_crossval_sets +from parasect.core.writers import write_list def parse_arguments() -> Namespace: @@ -33,6 +37,8 @@ def parse_arguments() -> Namespace: help="Max attempts made for splitting data") parser.add_argument("-t", "--taxonomic_rank", default="family", type=str, help="Taxonomic rank to split on") + parser.add_argument('-f', "--fold_cross_validation", default=3, type=int, + help="Fold crossvalidation") mode_group = parser.add_mutually_exclusive_group() mode_group.add_argument('--first_only', action='store_true', @@ -51,114 +57,6 @@ def parse_arguments() -> Namespace: return arguments -class SubstrateSelectionMode(Enum): - FIRST_ONLY = 1 - FIRST_VALID = 2 - ALL = 3 - - @staticmethod - def get_mode_from_string(string) -> Optional["SubstrateSelectionMode"]: - """ - Convert a string to a SplitMode enum value. - - :param string: String representation of split mode - :type string: str - :return: Corresponding SplitMode, or None if invalid - :rtype: SubstrateSelectionMode - """ - string_to_split_mode = {s.name: s for s in SubstrateSelectionMode} - return string_to_split_mode.get(string.upper()) - - -def _count_first_valid_substrate(session: Session, cutoff: int, - included_domains: DomainScope = DomainScope.ALL) -> dict[Substrate, int]: - """ - Count the first valid substrate for each domain in the database, iteratively filtering - substrates that do not meet a minimum occurrence cutoff. - - This function performs the following steps: - - 1. Computes the total counts of all substrates across all domains, regardless of order. - 2. Identifies a set of candidate substrates that meet the specified `cutoff` globally. - 3. Iteratively assigns to each domain the first substrate (in the domain's list) that - is in the set of candidate substrates. - 4. After each iteration, any substrate whose assigned count falls below the `cutoff` - is removed from the candidate set, and the process repeats until no substrates are - pruned. - - This ensures that the returned counts only include substrates that are both globally - and locally valid as "first substrates" for a sufficient number of domains. - - :param session: database session - :type session: Session - :param cutoff: minimum occurrence cutoff - :type cutoff: int - :param included_domains: determines which domains are considered (fungal, bacterial, all) - :type included_domains: DomainScope - :return: mapping of substrate to substrate counts - :rtype: dict[Substrate, int] - """ - - # Step 1: start with all substrates meeting cutoff globally - domains = DomainScope.get_domains(session, included_domains) - global_counts = _count_substrates_in_domains(domains, first_only=False) - valid_substrates = {s for s, c in global_counts.items() if c >= cutoff} - - changed = True - counts = {} - - while changed: - # Step 2: assign first valid substrate for each domain - domain_to_valid = {} - counts = {s: 0 for s in valid_substrates} - for d in domains: - for s in d.substrates: - if s in valid_substrates: - domain_to_valid[d] = s - counts[s] += 1 - break - else: - # No valid substrate for this domain - domain_to_valid[d] = None - - # Step 3: prune those that fell below cutoff - demoted = {s for s, c in counts.items() if c < cutoff} - if demoted: - valid_substrates -= demoted - changed = True - else: - changed = False - - return counts - - -def _map_domains_to_first_valid(domains: Iterable[AdenylationDomain], - included_substrates: set[Substrate]): - """ - Assign to each domain the first substrate from `included_substrates` that appears - in its substrate list. Domains with no matching substrate are assigned None. - - :param domains: Domains to process. - :type domains: Iterable[AdenylationDomain] - :param included_substrates: Substrates considered valid for assignment. - :type included_substrates: set[Substrate] - :return: Mapping of domains to their first valid substrate or None. - :rtype: dict[AdenylationDomain, Optional[Substrate]] - """ - domain_to_first_valid = {} - - for d in domains: - for s in d.substrates: - if s in included_substrates: - domain_to_first_valid[d] = s - break - else: - # No valid substrate found - domain_to_first_valid[d] = None - - return domain_to_first_valid - - def get_clades(session: Session, rank: Rank, included_domains: DomainScope = DomainScope.ALL) -> dict[tuple[str, ...], set[AdenylationDomain]]: """Group domains by clades at the specified taxonomic rank, accounting for overlapping clade memberships. @@ -207,57 +105,6 @@ def get_clades(session: Session, rank: Rank, return clade_group_to_domains -def _count_substrates_in_domains(domains: Iterable[AdenylationDomain], - first_only: bool) -> dict[Substrate, int]: - """Count substrates in a collection of domains. - - :param domains: collection of unique adenylation domains - :type domains: Iterable[AdenylationDomain] - :param first_only: if True, only count the first substrate for each domain. - :type first_only: bool - :return: dictionary mapping substrate to substrate counts - :rtype: dict[Substrate, int] - """ - counts: dict[Substrate, int] = {} - - for domain in domains: - for substrate in domain.substrates: - if substrate not in counts: - counts[substrate] = 0 - counts[substrate] += 1 - - if first_only: - break - - return counts - - -def count_substrates(session: Session, first_only: bool, cutoff: int = 0, - included_domains: DomainScope = DomainScope.ALL) -> dict[Substrate, int]: - """Count occurrences of substrates across all domains, optionally filtering by cutoff. - - :param session: database session - :type session: Session - :param first_only: if given, only count the first substrate for each domain - :type first_only: bool - :param cutoff: only include substrates that occur at least this many times - :type cutoff: int - :param included_domains: determines which domains are considered (fungal, bacterial, all) - :type included_domains: DomainScope - :return: dictionary mapping substrate to substrate counts - :rtype: dict[Substrate, int] - """ - domains = DomainScope.get_domains(session, included_domains) - - substrate_to_count = _count_substrates_in_domains(domains, first_only) - - for substrate, count in list(substrate_to_count.items()): - if count < cutoff: - del substrate_to_count[substrate] - - return substrate_to_count - - def get_counts_per_clade_first_valid(clade_group_to_domains: dict[tuple[str, ...], set[AdenylationDomain]], included_substrates: set[Substrate]) -> dict[tuple[str, ...], dict[Substrate, int]]: """ @@ -272,7 +119,8 @@ def get_counts_per_clade_first_valid(clade_group_to_domains: dict[tuple[str, ... """ counts_per_clade = {} for clade, domains in clade_group_to_domains.items(): - domain_to_valid = _map_domains_to_first_valid(domains, included_substrates) + domain_to_valid = map_domains_to_substrates(domains, included_substrates, + selection_mode=SubstrateSelectionMode.FIRST_VALID) substrate_counts = {s: 0 for s in included_substrates} for s in domain_to_valid.values(): if s is not None: @@ -298,7 +146,7 @@ def get_counts_per_clade(clade_group_to_domains: dict[tuple[str, ...], set[Adeny counts_per_clade: dict[tuple[str, ...], dict[Substrate, int]] = {} for clade, domains in clade_group_to_domains.items(): - substrate_to_count = _count_substrates_in_domains(domains, first_only=first_only) + substrate_to_count = count_substrates_in_domains(domains, first_only=first_only) for substrate in list(substrate_to_count.keys()): if substrate not in included_substrates: del substrate_to_count[substrate] @@ -308,24 +156,6 @@ def get_counts_per_clade(clade_group_to_domains: dict[tuple[str, ...], set[Adeny return counts_per_clade -def check_split_possible(clade_substrate_counts: dict[tuple[str, ...], dict], substrates: set[Substrate]) -> bool: - """ - Check if all substrates appear in at least two clades, required for splitting train/test sets. - - :param clade_substrate_counts: dict mapping clade groups → substrate counts - :type clade_substrate_counts: dict[tuple[str, ...], dict] - :param substrates: set of substrates to check - :type substrates: set[Substrate] - :return: True if split possible, False otherwise - """ - for sub in substrates: - clades_with_sub = [clade for clade, counts in clade_substrate_counts.items() if counts.get(sub, 0) > 0] - if len(clades_with_sub) < 2: - print(f"Substrate {sub} occurs in less than 2 clades: {len(clades_with_sub)}") - return False - return True - - def split_on_rank(session: Session, rank: Rank, cutoff: int = 6, @@ -368,7 +198,7 @@ def split_on_rank(session: Session, included_domains=included_domains) elif split_mode == SubstrateSelectionMode.FIRST_VALID: - substrate_to_count = _count_first_valid_substrate(session, cutoff, included_domains=included_domains) + substrate_to_count = count_first_valid_substrate(session, cutoff, included_domains=included_domains) else: raise ValueError(f"Unknown split mode: {split_mode}") @@ -481,6 +311,7 @@ def total_error(counts): domain_assignment[domain] = side break + return { "assignment": coverage_assignment, "substrate_counts": substrate_counts, @@ -530,6 +361,10 @@ def main(): substrate_counts = result["substrate_counts"] domain_assignment = result["domain_assignment"] + train_domains = [domain for domain, side in domain_assignment.items() if side == "train"] + domain_to_substrates = map_domains_to_substrates(train_domains, set(substrate_counts.keys()), split_mode) + + with open(train_out, 'w') as train, open(test_out, 'w') as test: for domain, assignment in domain_assignment.items(): if assignment == "train": @@ -549,11 +384,36 @@ def main(): else: raise ValueError(f"Unknown clade assignment: {assignment}") + included_substrates_file = os.path.join(args.output, "included_substrates.txt") + included_substrates = list(substrate_counts.keys()) + included_substrates.sort() + write_list(included_substrates, included_substrates_file) + with open(substrate_splits, 'w') as substrates_out: substrates_out.write("substrate_name\ttrain\ttest\n") for substrate, counts in substrate_counts.items(): substrates_out.write(f"{substrate.name}\t{counts['train']}\t{counts['test']}\n") + if split_mode == SubstrateSelectionMode.ALL: + label_sets = [] + for domain in train_domains: + substrates = domain_to_substrates[domain] + label_sets.append(substrates) + + binary_labels, labels = binarise_data(label_sets) + binary_labels = list(binary_labels) + + + make_crossval_sets(train_domains, [domain_to_substrates[d] for d in train_domains], args.output, + binary_labels=binary_labels, + fold_validation=args.fold_cross_validation, + selection_mode=split_mode) + + else: + + make_crossval_sets(train_domains, [domain_to_substrates[d] for d in train_domains], args.output, + fold_validation=args.fold_cross_validation, selection_mode=split_mode) + # Sum across all substrates total_train = sum(ct["train"] for ct in substrate_counts.values()) total_test = sum(ct["test"] for ct in substrate_counts.values()) diff --git a/src/parasect/model_training/train_test_splits/split_on_substrate.py b/src/parasect/model_training/train_test_splits/split_on_substrate.py new file mode 100644 index 0000000..c973f4c --- /dev/null +++ b/src/parasect/model_training/train_test_splits/split_on_substrate.py @@ -0,0 +1,192 @@ +from argparse import ArgumentParser, Namespace +import os + +from sklearn.model_selection import train_test_split +from iterstrat.ml_stratifiers import MultilabelStratifiedShuffleSplit +from sqlalchemy.orm import Session +from sqlalchemy import create_engine +import numpy as np + +from parasect.model_training.train_test_splits.domain_scope import DomainScope +from parasect.model_training.train_test_splits.substrate_selection import SubstrateSelectionMode, count_substrates, \ + count_first_valid_substrate, map_domains_to_substrates +from parasect.model_training.train_test_splits.multilabel_stratification import binarise_data +from parasect.core.writers import write_list +from parasect.model_training.train_test_splits.crossvalidation import make_crossval_sets + + +def parse_arguments() -> Namespace: + """Parse arguments from command line + + :return: Arguments + :rtype: Namespace + """ + parser = ArgumentParser(description="Split domains into train and test set based on taxonomy") + + parser.add_argument("-db", "--database", type=str, required=True, + help="Path to PARASECT database") + parser.add_argument("-o", "--output", required=True, type=str, + help="Output directory") + parser.add_argument("-c", '--cutoff', default=6, type=int, + help="Minimum substrate count for inclusion") + parser.add_argument("-r", '--test_ratio', default=0.25, type=float, + help="Target test set size") + parser.add_argument('-f', "--fold_cross_validation", default=3, type=int, + help="Fold crossvalidation") + + mode_group = parser.add_mutually_exclusive_group() + mode_group.add_argument('--first_only', action='store_true', + help="Count only the first substrate per domain") + mode_group.add_argument('--first_valid', action='store_true', + help="Count only the first valid substrate per domain") + + domain_group = parser.add_mutually_exclusive_group() + domain_group.add_argument('--fungal_only', action='store_true', + help="Only consider fungal domains") + domain_group.add_argument('--bacterial_only', action='store_true', + help="Only consider bacterial domains") + + arguments = parser.parse_args() + + return arguments + + +def split_on_substrate(session: Session, + out_dir: str, + selection_mode: SubstrateSelectionMode = SubstrateSelectionMode.ALL, + included_domains: DomainScope = DomainScope.ALL, + cutoff: int = 6, + test_size: float = 0.25, + fold_cross_validation: int = 3): + + random_seed = 10012025 + domains = DomainScope.get_domains(session, included_domains) + + if selection_mode == SubstrateSelectionMode.FIRST_VALID: + substrate_to_count = count_first_valid_substrate(session, cutoff, included_domains) + elif selection_mode == SubstrateSelectionMode.FIRST_ONLY: + substrate_to_count = count_substrates(session, first_only=True, cutoff=cutoff, + included_domains=included_domains) + elif selection_mode == SubstrateSelectionMode.ALL: + + substrate_to_count = count_substrates(session, first_only=False, cutoff=cutoff, + included_domains=included_domains) + else: + raise ValueError(f"Unknown substrate selection mode: {selection_mode}") + + included_substrates = set(substrate_to_count.keys()) + domain_to_substrates = map_domains_to_substrates(domains, included_substrates=included_substrates, + selection_mode=selection_mode) + domain_to_substrates = { + domain: substrate + for domain, substrate in domain_to_substrates.items() + if substrate is not None + } + + domains = list(domain_to_substrates.keys()) + + if selection_mode == SubstrateSelectionMode.ALL: + label_sets = [] + for domain in domains: + substrates = domain_to_substrates[domain] + label_sets.append(substrates) + + binary_labels, labels = binarise_data(label_sets) + + train_test_splitter = MultilabelStratifiedShuffleSplit(n_splits=1, test_size=test_size, random_state=25051989) + train = [] + test = [] + train_y = [] + + for train_x, test_x in train_test_splitter.split(domains, binary_labels): + + for idx in train_x: + train.append(domains[idx]) + train_y.append(binary_labels[idx]) + + for idx in test_x: + test.append(domains[idx]) + + make_crossval_sets(train, [domain_to_substrates[d] for d in train], out_dir, binary_labels=train_y, + fold_validation=fold_cross_validation, selection_mode=selection_mode) + + else: + labels = [] + for domain in domains: + substrate = domain_to_substrates[domain] + labels.append(substrate) + + labels = np.array(labels) + + train, test = train_test_split(domains, stratify=labels, test_size=test_size, random_state=random_seed) + make_crossval_sets(train, [domain_to_substrates[d] for d in train], out_dir, + fold_validation=fold_cross_validation, selection_mode=selection_mode) + + out_train = os.path.join(out_dir, 'train.txt') + out_test = os.path.join(out_dir, 'test.txt') + + write_list([d.get_name() for d in train], out_train) + write_list([d.get_name() for d in test], out_test) + + substrate_counts = {s: {"train": 0, "test": 0} for s in included_substrates} + + for domain, substrates in domain_to_substrates.items(): + if selection_mode == SubstrateSelectionMode.ALL: + for substrate in substrates: + if domain in train: + substrate_counts[substrate]["train"] += 1 + elif domain in test: + substrate_counts[substrate]["test"] += 1 + else: + raise ValueError(f"Unassigned domain: {domain.get_name()}") + else: + if domain in train: + substrate_counts[substrates]["train"] += 1 + elif domain in test: + substrate_counts[substrates]["test"] += 1 + else: + raise ValueError(f"Unassigned domain: {domain.get_name()}") + + substrate_splits = os.path.join(out_dir, "substrate_splits.txt") + + with open(substrate_splits, 'w') as substrates_out: + substrates_out.write("substrate_name\ttrain\ttest\n") + for substrate, counts in substrate_counts.items(): + substrates_out.write(f"{substrate.name}\t{counts['train']}\t{counts['test']}\n") + + included_substrates_file = os.path.join(out_dir, "included_substrates.txt") + included_substrates = list(substrate_counts.keys()) + included_substrates.sort() + write_list(included_substrates, included_substrates_file) + + +def main(): + args = parse_arguments() + + if args.first_only: + selection_mode = SubstrateSelectionMode.FIRST_ONLY + elif args.first_valid: + selection_mode = SubstrateSelectionMode.FIRST_VALID + else: + selection_mode = SubstrateSelectionMode.ALL + + if args.fungal_only: + included_domains = DomainScope.FUNGAL_ONLY + elif args.bacterial_only: + included_domains = DomainScope.BACTERIAL_ONLY + else: + included_domains = DomainScope.ALL + + if not os.path.exists(args.output): + os.mkdir(args.output) + + engine = create_engine(f"sqlite:///{args.database}") + + with Session(engine) as session: + split_on_substrate(session, args.output, selection_mode=selection_mode, included_domains=included_domains, + test_size=args.test_ratio, cutoff=args.cutoff, + fold_cross_validation=args.fold_cross_validation) + + +if __name__ == "__main__": + main() diff --git a/src/parasect/model_training/train_test_splits/substrate_selection.py b/src/parasect/model_training/train_test_splits/substrate_selection.py new file mode 100644 index 0000000..32106c0 --- /dev/null +++ b/src/parasect/model_training/train_test_splits/substrate_selection.py @@ -0,0 +1,186 @@ +from typing import Optional, Iterable, Union +from enum import Enum + +from sqlalchemy.orm import Session + +from parasect.database.build_database import Substrate, AdenylationDomain + +from .domain_scope import DomainScope + + +class SubstrateSelectionMode(Enum): + FIRST_ONLY = 1 + FIRST_VALID = 2 + ALL = 3 + + @staticmethod + def get_mode_from_string(string) -> Optional["SubstrateSelectionMode"]: + """ + Convert a string to a SplitMode enum value. + + :param string: String representation of split mode + :type string: str + :return: Corresponding SplitMode, or None if invalid + :rtype: SubstrateSelectionMode + """ + string_to_split_mode = {s.name: s for s in SubstrateSelectionMode} + return string_to_split_mode.get(string.upper()) + + +def count_first_valid_substrate(session: Session, cutoff: int, + included_domains: DomainScope = DomainScope.ALL) -> dict[Substrate, int]: + """ + Count the first valid substrate for each domain in the database, iteratively filtering + substrates that do not meet a minimum occurrence cutoff. + + This function performs the following steps: + + 1. Computes the total counts of all substrates across all domains, regardless of order. + 2. Identifies a set of candidate substrates that meet the specified `cutoff` globally. + 3. Iteratively assigns to each domain the first substrate (in the domain's list) that + is in the set of candidate substrates. + 4. After each iteration, any substrate whose assigned count falls below the `cutoff` + is removed from the candidate set, and the process repeats until no substrates are + pruned. + + This ensures that the returned counts only include substrates that are both globally + and locally valid as "first substrates" for a sufficient number of domains. + + :param session: database session + :type session: Session + :param cutoff: minimum occurrence cutoff + :type cutoff: int + :param included_domains: determines which domains are considered (fungal, bacterial, all) + :type included_domains: DomainScope + :return: mapping of substrate to substrate counts + :rtype: dict[Substrate, int] + """ + + # Step 1: start with all substrates meeting cutoff globally + domains = DomainScope.get_domains(session, included_domains) + global_counts = count_substrates_in_domains(domains, first_only=False) + valid_substrates = {s for s, c in global_counts.items() if c >= cutoff} + + changed = True + counts = {} + + while changed: + # Step 2: assign first valid substrate for each domain + domain_to_valid = {} + counts = {s: 0 for s in valid_substrates} + for d in domains: + for s in d.substrates: + if s in valid_substrates: + domain_to_valid[d] = s + counts[s] += 1 + break + else: + # No valid substrate for this domain + domain_to_valid[d] = None + + # Step 3: prune those that fell below cutoff + demoted = {s for s, c in counts.items() if c < cutoff} + if demoted: + valid_substrates -= demoted + changed = True + else: + changed = False + + return counts + + +def count_substrates_in_domains(domains: Iterable[AdenylationDomain], + first_only: bool) -> dict[Substrate, int]: + """Count substrates in a collection of domains. + + :param domains: collection of unique adenylation domains + :type domains: Iterable[AdenylationDomain] + :param first_only: if True, only count the first substrate for each domain. + :type first_only: bool + :return: dictionary mapping substrate to substrate counts + :rtype: dict[Substrate, int] + """ + counts: dict[Substrate, int] = {} + + for domain in domains: + for substrate in domain.substrates: + if substrate not in counts: + counts[substrate] = 0 + counts[substrate] += 1 + + if first_only: + break + + return counts + + +def count_substrates(session: Session, first_only: bool, cutoff: int = 0, + included_domains: DomainScope = DomainScope.ALL) -> dict[Substrate, int]: + """Count occurrences of substrates across all domains, optionally filtering by cutoff. + + :param session: database session + :type session: Session + :param first_only: if given, only count the first substrate for each domain + :type first_only: bool + :param cutoff: only include substrates that occur at least this many times + :type cutoff: int + :param included_domains: determines which domains are considered (fungal, bacterial, all) + :type included_domains: DomainScope + :return: dictionary mapping substrate to substrate counts + :rtype: dict[Substrate, int] + """ + domains = DomainScope.get_domains(session, included_domains) + + substrate_to_count = count_substrates_in_domains(domains, first_only) + + for substrate, count in list(substrate_to_count.items()): + if count < cutoff: + del substrate_to_count[substrate] + + return substrate_to_count + + +def map_domains_to_substrates(domains: Iterable[AdenylationDomain], + included_substrates: set[Substrate], + selection_mode: SubstrateSelectionMode) -> \ + dict[AdenylationDomain, Union[Optional[list[Substrate]], Optional[Substrate]]]: + """ + Assign to each domain one or more substrates. Domains with no matching substrate are assigned None. + + :param domains: Domains to process. + :type domains: Iterable[AdenylationDomain] + :param included_substrates: Substrates considered valid for assignment. + :type included_substrates: set[Substrate] + :param selection_mode: substrate selection mode (consider the first valid substrate, only the first substrate, + or all substrates + :return: Mapping of domains to their substrate(s) or None. + :rtype: dict[AdenylationDomain, Union[Optional[list[Substrate]], Optional[Substrate]]] + """ + + domain_to_substrate = {} + + for domain in domains: + if selection_mode == SubstrateSelectionMode.FIRST_VALID: + for substrate in domain.substrates: + if substrate in included_substrates: + domain_to_substrate[domain] = substrate + break + else: + # No valid substrate found + domain_to_substrate[domain] = None + elif selection_mode == SubstrateSelectionMode.FIRST_ONLY: + substrate = domain.substrates[0] + if substrate in included_substrates: + domain_to_substrate[domain] = substrate + else: + domain_to_substrate[domain] = None + elif selection_mode == SubstrateSelectionMode.ALL: + domain_to_substrate[domain] = [] + for substrate in domain.substrates: + if substrate in included_substrates: + domain_to_substrate[domain].append(substrate) + + if not domain_to_substrate[domain]: + domain_to_substrate[domain] = None + + return domain_to_substrate From 9ec9f2fcce34a7b123bdd4f07a800ee84b41b8f2 Mon Sep 17 00:00:00 2001 From: "Terlouw, Barbara" Date: Wed, 17 Sep 2025 09:30:22 +0200 Subject: [PATCH 49/65] Add code for training PARAS and PARASECT --- setup.cfg | 4 +- src/parasect/core/chem.py | 66 ++++ src/parasect/core/pca.py | 29 +- src/parasect/core/writers.py | 12 +- .../__init__.py | 0 .../taxonomy/__init__.py | 0 src/parasect/model_training/pca/build_pca.py | 33 +- .../model_training/pca/visualize_pca.py | 293 ++++++++++++++++++ .../model_training/rf/crossvalidation.py | 129 ++++++++ src/parasect/model_training/rf/test_rf.py | 142 +++++++++ src/parasect/model_training/rf/train_rf.py | 227 +++++++++++++- 11 files changed, 903 insertions(+), 32 deletions(-) rename src/parasect/model_training/{data_preparation => data_processing}/__init__.py (100%) rename src/parasect/model_training/{data_preparation => data_processing}/taxonomy/__init__.py (100%) create mode 100644 src/parasect/model_training/pca/visualize_pca.py create mode 100644 src/parasect/model_training/rf/crossvalidation.py create mode 100644 src/parasect/model_training/rf/test_rf.py diff --git a/setup.cfg b/setup.cfg index e3360a6..4571042 100644 --- a/setup.cfg +++ b/setup.cfg @@ -45,6 +45,8 @@ install_requires = scikit-learn==1.2.0 ncbi-acc-download>=0.2.5 sqlalchemy + iterative-stratification==0.1.9 + imblearn==0.12.4 # Random options zip_safe = false @@ -138,5 +140,5 @@ max-line-length = 120 max-complexity = 20 import-order-style = pycharm application-import-names = - parsect + parasect tests \ No newline at end of file diff --git a/src/parasect/core/chem.py b/src/parasect/core/chem.py index 9404612..9c2ca43 100644 --- a/src/parasect/core/chem.py +++ b/src/parasect/core/chem.py @@ -5,12 +5,15 @@ import os from typing import List, Dict from math import isclose +from collections import Counter from pikachu.fingerprinting.ecfp_4 import ECFP from pikachu.general import read_smiles from pikachu.fingerprinting.similarity import get_jaccard_index from pikachu.errors import StructureError +from parasect.database.build_database import Substrate + def parse_smiles_mapping(path_in: str) -> Dict[str, str]: """Parse a name to SMILES mapping from a file. @@ -87,3 +90,66 @@ def smiles_to_fingerprint(smiles: str) -> set[int]: fingerprint = ecfp.fingerprint return fingerprint + + +def get_fingerprint_hashes(substrates: set[Substrate], fingerprint_size: int) -> list[int]: + """Return list of fingerprint hashes sorted by count + + :param substrates: set of substrates from the PARASECT database + :type substrates: set[Substrate] + :param fingerprint_size: size of fingerprint + :type fingerprint_size: int + :return: list of hashes + :rtype: list[int] + """ + hashes = [] + + for substrate in substrates: + for chem_hash in substrate.fingerprint: + hashes.append(chem_hash) + + counts = Counter(hashes) + + hashes = [] + + for fingerprint_hash, count in counts.most_common(fingerprint_size): + hashes.append(fingerprint_hash) + + return hashes + + +def fingerprint_to_bitvector(hashes: list[int], fingerprint: set[int]) -> list[int]: + """Return bitvector from fingerprint and list of included hashes + + :param hashes: list of included hashes representing substrate training set + :type hashes: list[int] + :param fingerprint: fingerprint for substrate of interest + :type fingerprint: set[int] + :return: bitvector representing substrate of interest + :rtype: list[int] + """ + bitvector = [] + for fingerprint_hash in hashes: + if fingerprint_hash in fingerprint: + bitvector.append(1) + else: + bitvector.append(0) + + return bitvector + + +def smiles_to_bitvector(hashes: list[int], smiles: str) -> list[int]: + """Return bitvector from SMILES string + + :param hashes: list[int] + :type hashes: list + :param smiles: SMILES string + :type smiles: str + :return: bitvector + :rtype: list[int] + """ + + fingerprint = smiles_to_fingerprint(smiles) + bitvector = fingerprint_to_bitvector(hashes, fingerprint) + + return bitvector diff --git a/src/parasect/core/pca.py b/src/parasect/core/pca.py index af9b8f3..780a0c9 100644 --- a/src/parasect/core/pca.py +++ b/src/parasect/core/pca.py @@ -1,5 +1,5 @@ import os -from argparse import ArgumentParser, Namespace +from typing import Optional from sklearn.decomposition import PCA import numpy as np from joblib import dump @@ -7,7 +7,8 @@ from parasect.core.parsing import iterate_over_dir, parse_esm_embedding -def esm_to_pca(esm_dir: str, out_dir: str, n_components: int = 500, store_pca: bool = False) -> None: +def esm_to_pca(esm_dir: str, out_dir: str, n_components: int = 500, store_pca: bool = False, + prefix: str = "all_domains", domain_names: Optional[list[str]] = None) -> None: """Store transformed features to output :param esm_dir: directory containing files, with each file containing precomputed esm embedding for a domain extended signature @@ -18,10 +19,15 @@ def esm_to_pca(esm_dir: str, out_dir: str, n_components: int = 500, store_pca: b :type n_components: int :param store_pca: if True, store PCA model as well as transformed features. Default: False :type store_pca: bool + :param prefix: prefix for file + :type prefix: str + :param domain_names: if given, only include these domains + :type domain_names: Optional[list[str]] """ domain_nr = 0 - for _ in iterate_over_dir(esm_dir, "_esm.tsv"): - domain_nr += 1 + for domain_name, domain_path in iterate_over_dir(esm_dir, "_esm.tsv"): + if domain_names is None or domain_name in domain_names: + domain_nr += 1 feature_nr = 1280 * 34 esm_array = np.zeros(shape=(domain_nr, feature_nr)) @@ -29,19 +35,20 @@ def esm_to_pca(esm_dir: str, out_dir: str, n_components: int = 500, store_pca: b domains: list[str] = [] print("Loading data...") for domain_name, domain_path in iterate_over_dir(esm_dir, "_esm.tsv"): - domains.append(domain_name) - esm_embedding = parse_esm_embedding(domain_path) - esm_array[counter] = esm_embedding - counter += 1 + if domain_names is None or domain_name in domain_names: + domains.append(domain_name) + esm_embedding = parse_esm_embedding(domain_path) + esm_array[counter] = esm_embedding + counter += 1 pca = PCA(n_components=n_components, random_state=10012025) print("Transforming data...") - pca.fit_transform(esm_array) + pca_features = pca.fit_transform(esm_array) if not os.path.exists(out_dir): os.mkdir(out_dir) - pcs = os.path.join(out_dir, f"pcs_{n_components}.txt") + pcs = os.path.join(out_dir, f"{prefix}_pcs_{n_components}.txt") with open(pcs, 'w') as out: out.write("domain_name") @@ -49,7 +56,7 @@ def esm_to_pca(esm_dir: str, out_dir: str, n_components: int = 500, store_pca: b out.write(f'\tpc_{i + 1}') out.write('\n') - for i, embedding in enumerate(esm_array): + for i, embedding in enumerate(pca_features): domain_name = domains[i] out.write(domain_name) for feature in embedding: diff --git a/src/parasect/core/writers.py b/src/parasect/core/writers.py index 745cdef..e20e421 100644 --- a/src/parasect/core/writers.py +++ b/src/parasect/core/writers.py @@ -1,3 +1,5 @@ +from typing import Any + from parasect.core.parasect_result import Result @@ -49,16 +51,18 @@ def write_fasta_file(fasta_dict: dict[str, str], path_out: str) -> None: fo.write(f">{header}\n{sequence}\n") -def write_list(list_of_things: list[str], out_file: str) -> None: +def write_list(list_of_things: list[Any], out_file: str, sort: bool = True) -> None: """Write a list of things to a file, one thing per line :param list_of_things: list of strings - :type list_of_things: list[str] + :type list_of_things: list[Any] :param out_file: path to output file :type out_file: str + :param sort: if True, sort list of things prior to writing + :type sort: bool """ - - list_of_things.sort() + if sort: + list_of_things.sort() with open(out_file, 'w') as out: for thing in list_of_things: diff --git a/src/parasect/model_training/data_preparation/__init__.py b/src/parasect/model_training/data_processing/__init__.py similarity index 100% rename from src/parasect/model_training/data_preparation/__init__.py rename to src/parasect/model_training/data_processing/__init__.py diff --git a/src/parasect/model_training/data_preparation/taxonomy/__init__.py b/src/parasect/model_training/data_processing/taxonomy/__init__.py similarity index 100% rename from src/parasect/model_training/data_preparation/taxonomy/__init__.py rename to src/parasect/model_training/data_processing/taxonomy/__init__.py diff --git a/src/parasect/model_training/pca/build_pca.py b/src/parasect/model_training/pca/build_pca.py index beb4816..eb12fe3 100644 --- a/src/parasect/model_training/pca/build_pca.py +++ b/src/parasect/model_training/pca/build_pca.py @@ -1,6 +1,11 @@ from argparse import ArgumentParser, Namespace +import os + +from sqlalchemy import create_engine +from sqlalchemy.orm import Session from parasect.core.pca import esm_to_pca +from parasect.model_training.train_test_splits.domain_scope import DomainScope def parse_arguments() -> Namespace: @@ -18,12 +23,38 @@ def parse_arguments() -> Namespace: help="Number of PCA components") parser.add_argument("-s", "--store_pca", action="store_true", help="If given, store PCA model") + parser.add_argument("-db", "--database", type=str, default=None, help="Path to PARASECT database") + parser.add_argument("-f", "--fungal", action="store_true", + help="If given, also create a pca for fungal domains as well. -db must be given") + parser.add_argument("-b", "--bacterial", action="store_true", + help="If given, also create a pca for bacterial domains as well. -db must be given") arguments = parser.parse_args() + if arguments.fungal or arguments.bacterial: + assert arguments.database is not None + return arguments if __name__ == "__main__": args = parse_arguments() - esm_to_pca(esm_dir=args.esm, out_dir=args.out, n_components=args.n_components, store_pca=args.store_pca) + if not os.path.exists(args.out): + os.mkdir(args.out) + esm_to_pca(esm_dir=args.esm, out_dir=args.out, n_components=args.n_components, store_pca=args.store_pca, + prefix="all_domains") + + if args.database: + engine = create_engine(f"sqlite:///{args.database}") + + with Session(engine) as session: + + if args.fungal: + fungal_domains_names = [f.get_name() for f in DomainScope.get_domains(session, DomainScope.FUNGAL_ONLY)] + esm_to_pca(esm_dir=args.esm, out_dir=args.out, n_components=args.n_components, store_pca=args.store_pca, + prefix="fungal_domains", domain_names=fungal_domains_names) + + if args.bacterial: + bacterial_domains = [b.get_name() for b in DomainScope.get_domains(session, DomainScope.BACTERIAL_ONLY)] + esm_to_pca(esm_dir=args.esm, out_dir=args.out, n_components=args.n_components, store_pca=args.store_pca, + prefix="bacterial_domains", domain_names=bacterial_domains) diff --git a/src/parasect/model_training/pca/visualize_pca.py b/src/parasect/model_training/pca/visualize_pca.py new file mode 100644 index 0000000..2043781 --- /dev/null +++ b/src/parasect/model_training/pca/visualize_pca.py @@ -0,0 +1,293 @@ +import matplotlib.pyplot as plt +from matplotlib.pyplot import cm +import numpy as np +import argparse +import os + +from sqlalchemy.orm import Session +from sqlalchemy import create_engine + +from parasect.core.tabular import Tabular +from parasect.core.parsing import parse_list +from parasect.database.build_database import Substrate +from parasect.database.query_database import get_domains_from_synonym, get_substrates_from_name, \ + get_domains_from_taxonomic_rank +from parasect.model_training.train_test_splits.substrate_selection import SubstrateSelectionMode, \ + map_domains_to_substrates +from parasect.core.taxonomy import Rank + + +class PcaData: + def __init__(self, n_components): + self.domains = [] + self.labels = [] + self.n_components = n_components + self.vectors = [] + + @classmethod + def from_file(cls, session, pca_file, included_substrates: set[Substrate], + selection_mode: SubstrateSelectionMode = SubstrateSelectionMode.FIRST_ONLY, + by_clade: bool = False): + assert selection_mode in [SubstrateSelectionMode.FIRST_ONLY, SubstrateSelectionMode.FIRST_VALID] + pca_data = Tabular(pca_file) + domains = [] + substrates = [] + pca_vectors = [] + + for domain_name in pca_data.rows: + domain_synonym = domain_name.split('|')[0] + domain = get_domains_from_synonym(session, domain_synonym)[0] + domains.append(domain) + pca_vectors.append(list(map(float, pca_data.get_row_values(domain_name)[1:]))) + + domain_to_substrates = map_domains_to_substrates(domains, included_substrates, selection_mode) + + filtered_domains = [] + filtered_vectors = [] + + fungal_domains = get_domains_from_taxonomic_rank(session, Rank.KINGDOM, "Fungi") + bacterial_domains = get_domains_from_taxonomic_rank(session, Rank.DOMAIN, "Bacteria") + + for i, domain in enumerate(domains): + if domain_to_substrates[domain] is not None: + filtered_domains.append(domain) + if by_clade: + if domain in fungal_domains: + substrates.append("Fungal") + elif domain in bacterial_domains: + substrates.append("Bacterial") + else: + substrates.append("Unknown") + else: + substrates.append(domain_to_substrates[domain].name) + filtered_vectors.append(pca_vectors[i]) + + n_components = len(pca_vectors[0]) + pca_data = cls(n_components) + pca_data.set_labels_from_lists(substrates, filtered_domains) + pca_data.vectors = filtered_vectors + + return pca_data + + def set_labels_from_lists(self, substrates, domains): + self.labels = substrates + self.domains = domains + + def visualise(self, out_png, projection='2d', x=1, y=2, z=3, substrates=None, + domains_of_interest=None, domain_labels=None): + + fig = plt.figure(figsize=(15, 8)) + x -= 1 + y -= 1 + z -= 1 + + # plt.rcParams["figure.figsize"] = (10, 8) + + if not domains_of_interest: + + substrate_to_xy = {} + + if substrates: + for substrate in set(self.labels): + if substrate in substrates: + substrate_to_xy[substrate] = {'x': [], + 'y': [], + 'z': []} + labels = set() + for i, substrate in enumerate(self.labels): + if substrate in substrates: + substrate_to_xy[substrate]['x'].append(self.vectors[i][x]) + substrate_to_xy[substrate]['y'].append(self.vectors[i][y]) + substrate_to_xy[substrate]['z'].append(self.vectors[i][z]) + labels.add(substrate) + + else: + + for substrate in set(self.labels): + if substrates is not None: + if substrate in substrates: + substrate_to_xy[substrate] = {'x': [], + 'y': [], + 'z': []} + else: + + substrate_to_xy[substrate] = {'x': [], + 'y': [], + 'z': []} + + labels = set() + + for i, substrate in enumerate(self.labels): + substrate_to_xy[substrate]['x'].append(self.vectors[i][x]) + substrate_to_xy[substrate]['y'].append(self.vectors[i][y]) + substrate_to_xy[substrate]['z'].append(self.vectors[i][z]) + labels.add(substrate) + + if len(labels) <= 22: + colors = list(cm.tab20(np.linspace(0, 1, 20))) + colors = ['black'] + colors + ['blue'] + else: + colors = cm.nipy_spectral(np.linspace(0, 1, len(labels))) + + filtered_labels = sorted(labels) + + plt.gcf().subplots_adjust(left=0.05, right=0.45) + + if projection == '2d': + + for i, substrate in enumerate(filtered_labels): + color = colors[i] + plt.scatter(substrate_to_xy[substrate]['x'], substrate_to_xy[substrate]['y'], + label=substrate, color=color) + plt.legend(bbox_to_anchor=(1.05, 1), loc='upper left') + plt.savefig(out_png) + + elif projection == '3d': + ax = fig.add_subplot(projection='3d') + for i, substrate in enumerate(filtered_labels): + color = colors[i] + ax.scatter(substrate_to_xy[substrate]['x'], + substrate_to_xy[substrate]['y'], + substrate_to_xy[substrate]['z'], + label=substrate, color=color) + + ax.set_xlabel(f'PC {x + 1}') + ax.set_ylabel(f'PC {y + 1}') + ax.set_zlabel(f'PC {z + 1}') + + ax.legend(bbox_to_anchor=(1.05, 1.0), loc='upper left') + fig.savefig(out_png) + + else: + raise ValueError("Projection must be 2d or 3d") + + else: + if domain_labels: + assert len(domains_of_interest) == len(domain_labels) + + if len(domains_of_interest) == 2: + colors = ["lightsteelblue", "darksalmon"] #["gainsboro"] + elif len(domains_of_interest) <= 20: + colors = list(cm.tab20(np.linspace(0, 1, 20))) + else: + colors = cm.nipy_spectral(np.linspace(0, 1, len(domains_of_interest))) + + xs = [] + ys = [] + zs = [] + + for vector in self.vectors: + xs.append(vector[x]) + ys.append(vector[y]) + zs.append(vector[z]) + if projection == '2d': + plt.scatter(xs, ys, color="gainsboro") + elif projection == '3d': + fig = plt.figure() + ax = fig.add_subplot(projection='3d') + ax.scatter(xs, ys, zs, color="gainsboro") + else: + raise ValueError("Projection must be 2d or 3d") + + for i, domain in enumerate(domains_of_interest): + color = colors[i] + domain_index = self.domains.index(domain) + if domain_labels: + label = domain_labels[i] + else: + label = domain + domain_vector = self.vectors[domain_index] + xs = [domain_vector[x]] + ys = [domain_vector[y]] + zs = [domain_vector[z]] + + if projection == '2d': + plt.scatter(xs, ys, color=color, label=label) + elif projection == '3d': + ax.scatter(xs, ys, zs, color=color, label=label) + else: + raise ValueError("Projection must be 2d or 3d") + + if projection == '2d': + legend = plt.legend(loc='upper right') + plt.savefig(out_png, bbox_extra_artists=(legend, ), bbox_inches='tight') + plt.xlabel(f'PC {x + 1}') + plt.ylabel(f'PC {y + 1}') + elif projection == '3d': + ax.set_xlabel(f'PC {x + 1}') + ax.set_ylabel(f'PC {y + 1}') + ax.set_zlabel(f'PC {z + 1}') + + ax.legend(bbox_to_anchor=(1.05, 1.0), loc='upper left') + fig.savefig(out_png) + else: + raise ValueError("Projection must be 2d or 3d") + + plt.show() + plt.clf() + + + + +def parse_arguments(): + parser = argparse.ArgumentParser() + parser.add_argument('-pca', '--pca_file', type=str, required=True, help="File containing precomputed PCs.") + parser.add_argument('-v', '--projection', type=str, default='2d', help="Projection in PCA visualisation") + parser.add_argument('-x', type=int, default=1, help="PCA index to visualise in the x-direction") + parser.add_argument('-y', type=int, default=2, help="PCA index to visualise in the y-direction") + parser.add_argument('-z', type=int, default=3, help="PCA index to visualise in the z-direction") + parser.add_argument('-s', '--shown_substrates', type=str, nargs='*', default=None, help="Substrates to show") + parser.add_argument('-o', '--out', type=str, required=True, help="Path to output directory") + parser.add_argument('-p', '--prefix', type=str, default=None, help="Prefix") + parser.add_argument('-d', '--highlighted_domains', type=str, nargs='*', default=None, + help="Domains to highlight") + parser.add_argument('-l', '--domain_labels', type=str, nargs='*', default=None, help="Labels of domains of interest") + parser.add_argument('-i', '--included_substrates', type=str, required=True, help="Path to file with included substrates") + parser.add_argument('-db', '--database', type=str, required=True, help="Path to sql database") + parser.add_argument('-c', '--visualise_clades', action='store_true', + help="If given, visualise taxonomy instead of substrates") + + args = parser.parse_args() + return args + + +def run(): + args = parse_arguments() + if not os.path.exists(args.out): + os.mkdir(args.out) + + engine = create_engine(f"sqlite:///{args.database}") + + with Session(engine) as session: + included_substrate_names = parse_list(args.included_substrates) + included_substrates = set() + for name in included_substrate_names: + included_substrates.add(get_substrates_from_name(session, name)[0]) + + pca_data = PcaData.from_file(session, args.pca_file, included_substrates, by_clade=args.visualise_clades) + + if args.projection == '2d': + if args.prefix: + png_name = f'{args.prefix}_pocket_{args.x}_{args.y}.png' + else: + png_name = f'pocket_{args.x}_{args.y}.png' + elif args.projection == '3d': + if args.prefix: + png_name = f'{args.prefix}_pocket_{args.x}_{args.y}_{args.z}.png' + else: + png_name = f'pocket_{args.x}_{args.y}_{args.z}.png' + + else: + raise ValueError("Projection must be 2d or 3d") + + if args.highlighted_domains: + assert args.domain_labels and len(args.domain_labels) == len(args.highlighted_domains) + + png_out = os.path.join(args.out, png_name) + pca_data.visualise(png_out, projection=args.projection, x=args.x, y=args.y, z=args.z, + substrates=args.shown_substrates, + domains_of_interest=args.highlighted_domains, domain_labels=args.domain_labels) + + +if __name__ == "__main__": + run() diff --git a/src/parasect/model_training/rf/crossvalidation.py b/src/parasect/model_training/rf/crossvalidation.py new file mode 100644 index 0000000..005b512 --- /dev/null +++ b/src/parasect/model_training/rf/crossvalidation.py @@ -0,0 +1,129 @@ +import os +from enum import Enum +from typing import Optional + +from sqlalchemy.orm import Session +from sqlalchemy import create_engine +from argparse import ArgumentParser, Namespace + + +from parasect.core.parsing import iterate_over_dir, parse_list +from parasect.database.query_database import get_domains_from_synonym +from parasect.model_training.rf.train_rf import train_paras_signatures, train_paras_esm +from parasect.model_training.rf.test_rf import test_paras_signatures, test_paras_esm +from parasect.model_training.train_test_splits.domain_scope import DomainScope +from parasect.model_training.train_test_splits.substrate_selection import SubstrateSelectionMode + + +def parse_arguments() -> Namespace: + """Parse arguments from command line + + :return: Arguments + :rtype: Namespace + """ + parser = ArgumentParser(description="Split domains into train and test set based on taxonomy") + + parser.add_argument("-db", "--database", type=str, required=True, + help="Path to PARASECT database") + parser.add_argument("-c", "--crossval_folder", type=str, required=True, + help="Path to crossvalidation folder") + parser.add_argument("-o", "--output", required=True, type=str, + help="Output directory") + parser.add_argument("-p", "--esm_pca", type=str, default=None, + help="Path to PCA of ESM embeddings. If given, train in ESM PCA embedding mode") + + args = parser.parse_args() + + return args + + +class TrainingMode(Enum): + SIGNATURES = 1 + ESM_PCA = 2 + + +def do_crossvalidation(session: Session, crossvalidation_folder: str, out_dir: str, + esm_embeddings: Optional[str] = None) -> None: + """ + + :param session: + :type session: + :param crossvalidation_folder: + :type crossvalidation_folder: + :param out_dir: + :type out_dir: + :param esm_embeddings: + :type esm_embeddings: + :return: + :rtype: + """ + if not os.path.exists(out_dir): + os.mkdir(out_dir) + included_substrates_file = os.path.join(crossvalidation_folder, "included_substrates.txt") + crossvalidation_train_files = [] + crossvalidation_test_files = [] + if "_valid" in crossvalidation_folder: + selection_mode = SubstrateSelectionMode.FIRST_VALID + elif "_first" in crossvalidation_folder: + selection_mode = SubstrateSelectionMode.FIRST_ONLY + else: + selection_mode = SubstrateSelectionMode.FIRST_ONLY + + for file_name, file_path in iterate_over_dir(crossvalidation_folder, '.txt'): + if file_name.startswith("test_crossvalidation"): + crossvalidation_test_files.append(file_path) + if file_name.startswith("train_crossvalidation"): + crossvalidation_train_files.append(file_path) + + crossvalidation_train_files.sort() + crossvalidation_test_files.sort() + + assert len(crossvalidation_train_files) == len(crossvalidation_test_files) + + for i, train_file in enumerate(crossvalidation_train_files): + + test_file = crossvalidation_test_files[i] + + domain_names = parse_list(test_file) + domains = [] + for domain in domain_names: + synonym = domain.split('|')[0] + domains.append(get_domains_from_synonym(session, synonym)[0]) + + fungal_domains = list(set(DomainScope.get_domains(session, DomainScope.FUNGAL_ONLY)).intersection(set(domains))) + bacterial_domains = list(set(DomainScope.get_domains(session, DomainScope.BACTERIAL_ONLY)).intersection(set(domains))) + + if esm_embeddings is None: + model = train_paras_signatures(session, train_file, selection_mode, included_substrates_file) + else: + model = train_paras_esm(session, train_file, selection_mode, included_substrates_file, + esm_embeddings) + + crossval_dir = os.path.join(out_dir, f"crossvalidation_{i + 1}_all") + crossval_dir_fungal = os.path.join(out_dir, f"crossvalidation_{i + 1}_fungal") + crossval_dir_bacterial = os.path.join(out_dir, f"crossvalidation_{i + 1}_bacterial") + print(f"\nTesting all domains... (crossvalidation set {i + 1})") + if esm_embeddings is None: + test_paras_signatures(model, domains, included_substrates_file, crossval_dir) + else: + test_paras_esm(model, domains, esm_embeddings, included_substrates_file, crossval_dir) + if fungal_domains: + print(f"\nTesting fungal domains... (crossvalidation set {i + 1})") + if esm_embeddings is None: + test_paras_signatures(model, fungal_domains, included_substrates_file, crossval_dir_fungal) + else: + test_paras_esm(model, fungal_domains, esm_embeddings, included_substrates_file, crossval_dir_fungal) + if bacterial_domains: + print(f"\nTesting bacterial domains... (crossvalidation set {i + 1})") + if esm_embeddings is None: + test_paras_signatures(model, bacterial_domains, included_substrates_file, crossval_dir_bacterial) + else: + test_paras_esm(model, bacterial_domains, esm_embeddings, included_substrates_file, crossval_dir_bacterial) + + +if __name__ == "__main__": + args = parse_arguments() + + engine = create_engine(f"sqlite:///{args.database}") + with Session(engine) as session: + do_crossvalidation(session, args.crossval_folder, args.output, args.esm_pca) \ No newline at end of file diff --git a/src/parasect/model_training/rf/test_rf.py b/src/parasect/model_training/rf/test_rf.py new file mode 100644 index 0000000..d7e1678 --- /dev/null +++ b/src/parasect/model_training/rf/test_rf.py @@ -0,0 +1,142 @@ +import os + +from sklearn.ensemble import RandomForestClassifier +import numpy as np +from numpy.typing import NDArray + +from parasect.database.build_database import AdenylationDomain +from parasect.core.parsing import parse_list, parse_pcs +from parasect.core.featurisation import get_domain_features +from parasect.model_training.data_processing.plotting.confusion_matrix import plot_matrix, write_matrix + + +def write_accuracy(overall_accuracy, per_substrate_accuracy, out_file): + with open(out_file, 'w') as out: + out.write(f"substrate\taccuracy\n") + out.write(f"all\t{overall_accuracy:.3f}\n") + substrates = sorted(per_substrate_accuracy.keys()) + for substrate in substrates: + accuracy = per_substrate_accuracy[substrate] + if accuracy is not None: + out.write(f"{substrate}\t{accuracy:.3f}\n") + else: + out.write(f"{substrate}\tN/A\n") + + +def test_paras_signatures(classifier: RandomForestClassifier, + domains: list[AdenylationDomain], included_substrates_file: str, + out_dir: str) -> None: + """Test RF trained on PARAS signatures + + :param classifier: random forest classifier + :type classifier: RandomForestClassifier + :param domains: list of adenylation domains + :type domains: list[AdenylationDomain] + :param included_substrates_file: path to file containing included substrates + :type included_substrates_file: str + :param out_dir: path to output directory + :type out_dir: str + """ + if not os.path.exists(out_dir): + os.mkdir(out_dir) + + features = np.array([get_domain_features(domain.extended_signature) for domain in domains]) + predictions = classifier.predict(features) + + write_predictions(domains, predictions, included_substrates_file, out_dir) + + +def test_paras_esm(classifier: RandomForestClassifier, + domains: list[AdenylationDomain], + embeddings_file: str, included_substrates_file: str, out_dir: str) -> None: + """Test RF trained on PARAS signatures + + :param classifier: random forest classifier + :type classifier: RandomForestClassifier + :param domains: list of adenylation domains + :type domains: list[AdenylationDomain] + :param embeddings_file: path to file containing esm embeddings + :type embeddings_file: str + :param included_substrates_file: path to file containing included substrates + :type included_substrates_file: str + :param out_dir: path to output directory + :type out_dir: str + """ + if not os.path.exists(out_dir): + os.mkdir(out_dir) + + domains_pca, pca_data = parse_pcs(embeddings_file) + + name_to_row = {name: row for name, row in zip(domains_pca, pca_data)} + features = np.array([name_to_row[d.get_name()] for d in domains]) + + predictions = classifier.predict(features) + write_predictions(domains, predictions, included_substrates_file, out_dir) + + +def write_predictions(domains: list[AdenylationDomain], predictions: NDArray[np.str_], + included_substrates_file: str, + out_dir: str): + """Write predictions to output directory + + :param domains: list of adenylation domains + :type domains: list[AdenylationDomain] + :param predictions: predictions made by classifier + :type predictions: NDArray[np.str_] + :param included_substrates_file: path to file containing included substrates + :type included_substrates_file: str + :param out_dir: path to output directory + :type out_dir: str + """ + overall_correct = 0 + overall_incorrect = 0 + per_substrate_counts = {} # {substrate_name: [correct, total]} + + included_substrate_names = parse_list(included_substrates_file) + + for substrate in included_substrate_names: + per_substrate_counts[substrate] = [0, 0] + + substrate_nr = len(included_substrate_names) + + confusion_matrix = np.zeros(shape=(substrate_nr, substrate_nr)) + + for i, prediction in enumerate(predictions): + prediction_index = included_substrate_names.index(prediction) + substrate_names = [s.name for s in domains[i].substrates] + substrate_index = None + for substrate in substrate_names: + if substrate in included_substrate_names: + substrate_index = included_substrate_names.index(substrate) + break + + if substrate_index is not None: + confusion_matrix[prediction_index][substrate_index] += 1 + + if prediction in substrate_names: + overall_correct += 1 + else: + overall_incorrect += 1 + + for substrate in substrate_names: + if substrate in included_substrate_names: + per_substrate_counts[substrate][1] += 1 # total + if prediction == substrate: + per_substrate_counts[substrate][0] += 1 # correct + + # Compute accuracies + overall_accuracy = overall_correct / (overall_correct + overall_incorrect) + print(f"Overall accuracy: {overall_accuracy}") + per_substrate_accuracy = { + s: (correct / total if total > 0 else None) + for s, (correct, total) in per_substrate_counts.items() + } + + out_plot = os.path.join(out_dir, "confusion_matrix.svg") + out_matrix = os.path.join(out_dir, "confusion_matrix.txt") + out_accuracy = os.path.join(out_dir, "metrics.txt") + + plot_matrix(confusion_matrix, included_substrate_names, out_plot) + write_matrix(confusion_matrix, included_substrate_names, out_matrix) + + write_accuracy(overall_accuracy, per_substrate_accuracy, out_accuracy) diff --git a/src/parasect/model_training/rf/train_rf.py b/src/parasect/model_training/rf/train_rf.py index 4dca317..1466556 100644 --- a/src/parasect/model_training/rf/train_rf.py +++ b/src/parasect/model_training/rf/train_rf.py @@ -5,10 +5,12 @@ import numpy as np from sklearn.ensemble import RandomForestClassifier from sqlalchemy.orm import Session +from imblearn.under_sampling import RandomUnderSampler +from parasect.core.chem import get_fingerprint_hashes, fingerprint_to_bitvector from parasect.core.featurisation import get_domain_features -from parasect.database.query_database import get_domains_from_names, get_substrates_from_name -from parasect.core.parsing import parse_list +from parasect.database.query_database import get_domains_from_synonym, get_substrates_from_name +from parasect.core.parsing import parse_list, parse_pcs from parasect.model_training.train_test_splits.substrate_selection import SubstrateSelectionMode, \ map_domains_to_substrates @@ -32,15 +34,210 @@ def train_random_forest(features: NDArray[np.float64], labels: NDArray[np.str], class_weight="balanced", ) - model.fit(features, labels, sample_weight="balanced") + model.fit(features, labels) if out_path is not None: dump(model, out_path) return model -def train_rf_esm_pca(): - pass +def train_paras_esm(session: Session, domain_list: str, selection_mode: SubstrateSelectionMode, + included_substrates_file: str, pca_file: str, + out_path: Optional[str] = None) -> RandomForestClassifier: + """ + + :param session: database session + :type session: Session + :param selection_mode: determines which substrates are considered + :type selection_mode: SubstrateSelectionMode + :param included_substrates_file: path to file containing included substrates + :type included_substrates_file: str + :param domain_list: file path containing list of domains to train on + :type domain_list: str + :param pca_file: path to file containing pca of esm embeddings + :type pca_file: str + :param out_path: if given, save model to out path + :type out_path: Optional[str + + """ + domain_names = parse_list(domain_list) + + domains_pca, pca_data = parse_pcs(pca_file) + domain_to_pcs = { + domain: pca_data[i] + for i, domain in enumerate(domains_pca) + if domain in domain_names + } + + domains = [] + for domain in domain_names: + synonym = domain.split('|')[0] + domains.append(get_domains_from_synonym(session, synonym)[0]) + + domains.sort(key=lambda x: x.get_name()) + included_substrate_names = parse_list(included_substrates_file) + included_substrates = set() + for name in included_substrate_names: + included_substrates.add(get_substrates_from_name(session, name)[0]) + + domain_to_substrate = map_domains_to_substrates(domains, included_substrates, selection_mode=selection_mode) + + domain_to_substrate = { + domain: substrate + for domain, substrate in domain_to_substrate.items() + if substrate is not None + } + + features = np.array([domain_to_pcs[domain.get_name()] for domain in domains]) + labels = np.array([domain_to_substrate[domain].name for domain in domains]) + + classifier = train_random_forest(features, labels, out_path=out_path) + + return classifier + + +def train_parasect_signatures(session: Session, domain_list: str, + included_substrates_file: str, + bitvector_size: int = 256, + out_path: Optional[str] = None) -> tuple[RandomForestClassifier, list[int]]: + """Train PARASECT on extended signatures + + :param session: database session + :type session: Session + :param included_substrates_file: path to file containing included substrates + :type included_substrates_file: str + :param bitvector_size: size of bitvector + :type bitvector_size: int + :param domain_list: file path containing list of domains to train on + :type domain_list: str + :param out_path: if given, save model to out path + :type out_path: Optional[str + :returns: random forest classifier and sorted hashes used for bitvector construction + :rtype: tuple[RandomForestClassifier, list[int]] + + """ + + domain_names = parse_list(domain_list) + + domains = [] + for domain in domain_names: + synonym = domain.split('|')[0] + domains.append(get_domains_from_synonym(session, synonym)[0]) + + domains.sort(key=lambda x: x.get_name()) + included_substrate_names = parse_list(included_substrates_file) + included_substrates = set() + for name in included_substrate_names: + included_substrates.add(get_substrates_from_name(session, name)[0]) + + hashes = get_fingerprint_hashes(included_substrates, bitvector_size) + + domain_to_substrates = map_domains_to_substrates(domains, included_substrates, + selection_mode=SubstrateSelectionMode.ALL) + + domain_to_substrates = { + domain: substrates + for domain, substrates in domain_to_substrates.items() + if substrates is not None + } + train_x = [] + train_y = [] + for domain in domain_to_substrates: + for substrate in included_substrates: + domain_features = get_domain_features(domain.extended_signature) + substrate_features = fingerprint_to_bitvector(hashes, set(substrate.fingerprint)) + train_x.append(np.array(domain_features + substrate_features)) + if substrate in domain_to_substrates[domain]: + train_y.append(1) + else: + train_y.append(0) + + undersampler = RandomUnderSampler(random_state=25051989) + + features, labels = undersampler.fit_resample(train_x, train_y) + + classifier = train_random_forest(features, labels, out_path=out_path) + + return classifier, hashes + + +def train_parasect_esm(session: Session, domain_list: str, + included_substrates_file: str, + pca_file: str, + bitvector_size: int = 256, + out_path: Optional[str] = None) -> tuple[RandomForestClassifier, list[int]]: + """Train PARASECT on ESM features + + :param session: database session + :type session: Session + :param included_substrates_file: path to file containing included substrates + :type included_substrates_file: str + :param pca_file: path to pca file + :type pca_file: str + :param bitvector_size: size of bitvector + :type bitvector_size: int + :param domain_list: file path containing list of domains to train on + :type domain_list: str + :param out_path: if given, save model to out path + :type out_path: Optional[str + :returns: random forest classifier and sorted hashes used for bitvector construction + :rtype: tuple[RandomForestClassifier, list[int]] + + """ + + domain_names = parse_list(domain_list) + + domains_pca, pca_data = parse_pcs(pca_file) + domain_to_pcs = { + domain: pca_data[i] + for i, domain in enumerate(domains_pca) + if domain in domain_names + } + + domains = [] + for domain in domain_names: + synonym = domain.split('|')[0] + domains.append(get_domains_from_synonym(session, synonym)[0]) + + domains.sort(key=lambda x: x.get_name()) + included_substrate_names = parse_list(included_substrates_file) + included_substrates = set() + for name in included_substrate_names: + included_substrates.add(get_substrates_from_name(session, name)[0]) + + hashes = get_fingerprint_hashes(included_substrates, bitvector_size) + + domain_to_substrates = map_domains_to_substrates(domains, included_substrates, + selection_mode=SubstrateSelectionMode.ALL) + + domain_to_substrates = { + domain: substrates + for domain, substrates in domain_to_substrates.items() + if substrates is not None + } + + train_x = [] + train_y = [] + for domain in domain_to_substrates: + for substrate in included_substrates: + domain_features = domain_to_pcs[domain.get_name()] + substrate_features = fingerprint_to_bitvector(hashes, set(substrate.fingerprint)) + train_x.append(np.array(domain_features + substrate_features)) + if substrate in domain_to_substrates[domain]: + train_y.append(1) + else: + train_y.append(0) + + train_x = np.array(train_x) + train_y = np.array(train_y) + + undersampler = RandomUnderSampler(random_state=25051989) + + features, labels = undersampler.fit_resample(train_x, train_y) + + classifier = train_random_forest(features, labels, out_path=out_path) + + return classifier, hashes def train_paras_signatures(session: Session, domain_list: str, @@ -67,7 +264,10 @@ def train_paras_signatures(session: Session, domain_list: str, domain_names = parse_list(domain_list) - domains = get_domains_from_names(session, domain_names) + domains = [] + for domain in domain_names: + synonym = domain.split('|')[0] + domains.append(get_domains_from_synonym(session, synonym)[0]) domains.sort(key=lambda x: x.get_name()) included_substrate_names = parse_list(included_substrates_file) @@ -77,18 +277,15 @@ def train_paras_signatures(session: Session, domain_list: str, domain_to_substrate = map_domains_to_substrates(domains, included_substrates, selection_mode=selection_mode) + domain_to_substrate = { + domain: substrate + for domain, substrate in domain_to_substrate.items() + if substrate is not None + } + features = np.array([get_domain_features(domain.extended_signature) for domain in domains]) labels = np.array([domain_to_substrate[domain].name for domain in domains]) classifier = train_random_forest(features, labels, out_path=out_path) return classifier - - - - - - - - - From d7d8c7f80482c68efa3606bc98769dfba7b8c519 Mon Sep 17 00:00:00 2001 From: "Terlouw, Barbara" Date: Wed, 17 Sep 2025 09:31:21 +0200 Subject: [PATCH 50/65] Add code for confusion matrix plotting --- .../data_processing/plotting/__init__.py | 0 .../plotting/confusion_matrix.py | 39 +++++++++++++++++++ 2 files changed, 39 insertions(+) create mode 100644 src/parasect/model_training/data_processing/plotting/__init__.py create mode 100644 src/parasect/model_training/data_processing/plotting/confusion_matrix.py diff --git a/src/parasect/model_training/data_processing/plotting/__init__.py b/src/parasect/model_training/data_processing/plotting/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/src/parasect/model_training/data_processing/plotting/confusion_matrix.py b/src/parasect/model_training/data_processing/plotting/confusion_matrix.py new file mode 100644 index 0000000..c209ec8 --- /dev/null +++ b/src/parasect/model_training/data_processing/plotting/confusion_matrix.py @@ -0,0 +1,39 @@ +import pandas as pd +import scipy.cluster.hierarchy as hc +import matplotlib.pyplot as plt +import seaborn as sns +import scipy.spatial as sp + + +def write_matrix(matrix, labels, out_file): + with open(out_file, 'w') as out: + out.write('Predicted\\Actual\t') + out.write('\t'.join(labels)) + out.write("\n") + for i, aa in enumerate(labels): + out.write(f"{aa}") + for j, aa_2 in enumerate(labels): + out.write(f"\t{matrix[i][j]}") + out.write("\n") + + +def plot_matrix(matrix, labels, out_file, cluster=True): + data = pd.DataFrame(matrix, index=labels, columns=labels) + + cmap = sns.color_palette("rocket_r", as_cmap=True) + + if cluster: + + data_correlation = data.T.corr().fillna(0) + distance_matrix = 1 - data_correlation + distance_matrix = distance_matrix.clip(lower=0) + linkage = hc.linkage(sp.distance.squareform(distance_matrix, checks=False), method='average') + + clustermap = sns.clustermap(data, cmap=cmap, + row_linkage=linkage, col_linkage=linkage) + clustermap.fig.savefig(out_file) + plt.close(clustermap.fig) + else: + ax = sns.heatmap(data, cmap=cmap) + ax.get_figure().savefig(out_file) + plt.close(ax.get_figure()) From dc3d7a017078a9bcc77145a04ca2b9aa2fbc400c Mon Sep 17 00:00:00 2001 From: "Terlouw, Barbara" Date: Wed, 17 Sep 2025 09:32:50 +0200 Subject: [PATCH 51/65] Add dependencies for plotting --- setup.cfg | 2 ++ 1 file changed, 2 insertions(+) diff --git a/setup.cfg b/setup.cfg index 4571042..11e213d 100644 --- a/setup.cfg +++ b/setup.cfg @@ -47,6 +47,8 @@ install_requires = sqlalchemy iterative-stratification==0.1.9 imblearn==0.12.4 + pandas + seaborn # Random options zip_safe = false From d998c44e8a38981ab72e6e7cac1ae78ac8b9b2dc Mon Sep 17 00:00:00 2001 From: "Terlouw, Barbara" Date: Mon, 22 Sep 2025 10:56:17 +0200 Subject: [PATCH 52/65] Update code for training and testing paras and parasect --- src/parasect/core/parsing.py | 21 +- src/parasect/data/hashes.txt | 276 ++++++++++++ src/parasect/database/flatfiles_from_db.py | 11 + .../model_training/rf/crossvalidation.py | 94 +++- src/parasect/model_training/rf/test_rf.py | 413 +++++++++++++++++- src/parasect/model_training/rf/train_rf.py | 196 ++++++++- 6 files changed, 962 insertions(+), 49 deletions(-) create mode 100644 src/parasect/data/hashes.txt diff --git a/src/parasect/core/parsing.py b/src/parasect/core/parsing.py index f5a3169..7909f8f 100644 --- a/src/parasect/core/parsing.py +++ b/src/parasect/core/parsing.py @@ -84,12 +84,16 @@ def parse_raw_taxonomy(taxonomy_file: str) -> dict[str, list[str]]: return protein_to_taxonomy -def parse_list(list_file: str) -> list[str]: +def parse_list(list_file: str, sort: bool = True, unique: bool = True) -> list[str]: """Return list of things from file containing one item per line :param list_file: path to file containing one string per line :type list_file: str - :return: list of unique strings + :param sort: if True, sort output list + :type sort: bool + :param unique: if True, return only unique items + :type unique: bool + :return: list of things :rtype: list[str] """ string_list: list[str] = [] @@ -99,7 +103,13 @@ def parse_list(list_file: str) -> list[str]: if line: string_list.append(line) - return sorted(list(set(string_list))) + if unique: + string_list = list(set(string_list)) + + if sort: + string_list.sort() + + return string_list def parse_pcs(pca_file: str) -> tuple[list[str], NDArray[np.float64]]: @@ -108,7 +118,7 @@ def parse_pcs(pca_file: str) -> tuple[list[str], NDArray[np.float64]]: :param pca_file: file containing precomputed principal components :type pca_file: str :return: list of domain names and array of precomputed principal components for each domain - :rtype: tuple[list[str, NDArray[NDArray[np.float64]]]] + :rtype: tuple[list[str], NDArray[np.float64]] """ with open(pca_file, 'r') as pca_data: @@ -130,9 +140,10 @@ def parse_pcs(pca_file: str) -> tuple[list[str], NDArray[np.float64]]: line = line.strip() if line: line_data = line.split('\t') - pcs = line_data[1:] + pcs = list(map(float, line_data[1:])) array[counter] = pcs domains.append(line_data[0]) + counter += 1 return domains, array diff --git a/src/parasect/data/hashes.txt b/src/parasect/data/hashes.txt new file mode 100644 index 0000000..ef8f7c0 --- /dev/null +++ b/src/parasect/data/hashes.txt @@ -0,0 +1,276 @@ +829081502 +2283234228 +1258652603 +3977576644 +3522799069 +2778693672 +1560230541 +3883946894 +458548175 +191420530 +1048241268 +1315488206 +1237514124 +3079664652 +3538434540 +1644387425 +2693181564 +3785825467 +1221344109 +3890940231 +3759982330 +3349951008 +268216641 +4204299438 +1542250589 +2671826597 +4038888252 +4045618653 +1480508801 +1902793822 +3040137212 +1103368761 +117839297 +3898440133 +340599072 +1268049017 +443815054 +3102446724 +1683408722 +219781469 +1046016606 +265701480 +3470878254 +3129448451 +3384235106 +49561851 +2724517795 +3732059725 +3607054346 +416056630 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+3136581532 +427985703 +777816108 +68076729 +1637582397 +730777171 +4271065683 +732554456 +4277780958 +3647102077 +1451280134 +4056967817 +2144552660 +189804393 +1980337661 +2289199363 +3917346214 +3411179231 +1159568610 +3875084898 +3586473220 +4271699759 +3805258472 +266586866 +4196886440 +2972895811 +292064530 +3892140228 +2928621841 +989171348 +3334394151 +2279061544 +1272764611 +2117675079 +1370424664 +3879175800 +256887294 +1346074899 +1214274069 +160964508 +3483551529 +3557194931 +1230866494 +1625209851 +104093300 +753171451 +2685642216 +370408787 +1270405877 +3823138777 +1372194081 +1560482217 +3833800532 +34462953 +3154556277 +2253378427 diff --git a/src/parasect/database/flatfiles_from_db.py b/src/parasect/database/flatfiles_from_db.py index f54598c..ea1647d 100644 --- a/src/parasect/database/flatfiles_from_db.py +++ b/src/parasect/database/flatfiles_from_db.py @@ -5,6 +5,7 @@ from sqlalchemy.orm import Session from parasect.database.build_database import AdenylationDomain, Protein, Substrate +from parasect.core.writers import write_list def parse_arguments() -> Namespace: @@ -20,6 +21,16 @@ def parse_arguments() -> Namespace: return args +def write_substrate_names(session: Session, out_path: str) -> None: + all_substrates = list(session.scalars(select(Substrate)).all()) + write_list([s.name for s in all_substrates], out_path) + + +def write_domain_names(session: Session, out_path: str) -> None: + all_domains = list(session.scalars(select(AdenylationDomain)).all()) + write_list([d.get_name() for d in all_domains], out_path) + + def db_to_flatfiles(database_path: str, out_dir: str) -> None: """Write database entries to machine-readable flatfiles (.fasta, .tsv, .txt) diff --git a/src/parasect/model_training/rf/crossvalidation.py b/src/parasect/model_training/rf/crossvalidation.py index 005b512..3a6da03 100644 --- a/src/parasect/model_training/rf/crossvalidation.py +++ b/src/parasect/model_training/rf/crossvalidation.py @@ -9,8 +9,10 @@ from parasect.core.parsing import iterate_over_dir, parse_list from parasect.database.query_database import get_domains_from_synonym -from parasect.model_training.rf.train_rf import train_paras_signatures, train_paras_esm -from parasect.model_training.rf.test_rf import test_paras_signatures, test_paras_esm +from parasect.model_training.rf.train_rf import train_paras_signatures, train_paras_esm, \ + train_parasect_esm, train_parasect_signatures +from parasect.model_training.rf.test_rf import test_paras_signatures, test_paras_esm, test_parasect_signatures, \ + test_parasect_esm from parasect.model_training.train_test_splits.domain_scope import DomainScope from parasect.model_training.train_test_splits.substrate_selection import SubstrateSelectionMode @@ -29,8 +31,14 @@ def parse_arguments() -> Namespace: help="Path to crossvalidation folder") parser.add_argument("-o", "--output", required=True, type=str, help="Output directory") - parser.add_argument("-p", "--esm_pca", type=str, default=None, + parser.add_argument("-e", "--esm_pca", type=str, default=None, help="Path to PCA of ESM embeddings. If given, train in ESM PCA embedding mode") + parser.add_argument("-p", "--parasect", action="store_true", + help="If given, do crossvalidation for PARASECT models instead of PARAS models") + parser.add_argument("-n", "--n_components", type=int, default=100, + help="Number of ESM principal components to use for domain featurisation") + parser.add_argument('-b', "--bitvector_size", type=int, default=1024, + help="Size of ECFP4 bitvectors for substrate featurisation") args = parser.parse_args() @@ -43,7 +51,8 @@ class TrainingMode(Enum): def do_crossvalidation(session: Session, crossvalidation_folder: str, out_dir: str, - esm_embeddings: Optional[str] = None) -> None: + esm_embeddings: Optional[str] = None, parasect: bool = False, + bitvector_size: int = 256, n_components: int = 100) -> None: """ :param session: @@ -54,6 +63,12 @@ def do_crossvalidation(session: Session, crossvalidation_folder: str, out_dir: s :type out_dir: :param esm_embeddings: :type esm_embeddings: + :param parasect: if True, do crossvalidation for PARASECT models instead of PARAS models + :type parasect: bool + :param bitvector_size: Size of ECFP4 bitvectors for substrate featurisation + :type bitvector_size: int + :param n_components: Number of ESM principal components to use for domain featurisation + :type n_components: int :return: :rtype: """ @@ -67,7 +82,7 @@ def do_crossvalidation(session: Session, crossvalidation_folder: str, out_dir: s elif "_first" in crossvalidation_folder: selection_mode = SubstrateSelectionMode.FIRST_ONLY else: - selection_mode = SubstrateSelectionMode.FIRST_ONLY + selection_mode = SubstrateSelectionMode.ALL for file_name, file_path in iterate_over_dir(crossvalidation_folder, '.txt'): if file_name.startswith("test_crossvalidation"): @@ -93,32 +108,76 @@ def do_crossvalidation(session: Session, crossvalidation_folder: str, out_dir: s fungal_domains = list(set(DomainScope.get_domains(session, DomainScope.FUNGAL_ONLY)).intersection(set(domains))) bacterial_domains = list(set(DomainScope.get_domains(session, DomainScope.BACTERIAL_ONLY)).intersection(set(domains))) + hashes = [] if esm_embeddings is None: - model = train_paras_signatures(session, train_file, selection_mode, included_substrates_file) + if not parasect: + model = train_paras_signatures(session, train_file, selection_mode, included_substrates_file) + else: + model, hashes = train_parasect_signatures(session, train_file, included_substrates_file, + bitvector_size) + + print(f"Number of hashes: {len(hashes)}") else: - model = train_paras_esm(session, train_file, selection_mode, included_substrates_file, - esm_embeddings) + if not parasect: + model = train_paras_esm(session, train_file, selection_mode, included_substrates_file, + esm_embeddings, n_components) + else: + model, hashes = train_parasect_esm(session, train_file, included_substrates_file, esm_embeddings, + n_components, bitvector_size) + + print(f"Number of hashes: {len(hashes)}") crossval_dir = os.path.join(out_dir, f"crossvalidation_{i + 1}_all") crossval_dir_fungal = os.path.join(out_dir, f"crossvalidation_{i + 1}_fungal") crossval_dir_bacterial = os.path.join(out_dir, f"crossvalidation_{i + 1}_bacterial") + print(f"\nTesting all domains... (crossvalidation set {i + 1})") + if esm_embeddings is None: - test_paras_signatures(model, domains, included_substrates_file, crossval_dir) + if not parasect: + test_paras_signatures(model, domains, included_substrates_file, crossval_dir) + else: + assert selection_mode == SubstrateSelectionMode.ALL + test_parasect_signatures(session, model, domains, included_substrates_file, crossval_dir, hashes) + else: - test_paras_esm(model, domains, esm_embeddings, included_substrates_file, crossval_dir) - if fungal_domains: + if not parasect: + test_paras_esm(model, domains, esm_embeddings, included_substrates_file, crossval_dir, + n_components=n_components) + else: + test_parasect_esm(session, model, domains, included_substrates_file, esm_embeddings, crossval_dir, + hashes, n_components=n_components) + + if fungal_domains and set(fungal_domains) != set(domains): print(f"\nTesting fungal domains... (crossvalidation set {i + 1})") if esm_embeddings is None: - test_paras_signatures(model, fungal_domains, included_substrates_file, crossval_dir_fungal) + if not parasect: + test_paras_signatures(model, fungal_domains, included_substrates_file, crossval_dir_fungal) + else: + test_parasect_signatures(session, model, fungal_domains, included_substrates_file, + crossval_dir_fungal, hashes) else: - test_paras_esm(model, fungal_domains, esm_embeddings, included_substrates_file, crossval_dir_fungal) - if bacterial_domains: + if not parasect: + test_paras_esm(model, fungal_domains, esm_embeddings, included_substrates_file, crossval_dir_fungal) + else: + test_parasect_esm(session, model, fungal_domains, included_substrates_file, esm_embeddings, + crossval_dir_fungal, hashes, n_components=n_components) + if bacterial_domains and set(bacterial_domains) != set(domains): print(f"\nTesting bacterial domains... (crossvalidation set {i + 1})") if esm_embeddings is None: - test_paras_signatures(model, bacterial_domains, included_substrates_file, crossval_dir_bacterial) + if not parasect: + test_paras_signatures(model, bacterial_domains, included_substrates_file, crossval_dir_bacterial) + else: + test_parasect_signatures(session, model, bacterial_domains, included_substrates_file, + crossval_dir_bacterial, hashes) else: - test_paras_esm(model, bacterial_domains, esm_embeddings, included_substrates_file, crossval_dir_bacterial) + if not parasect: + test_paras_esm(model, bacterial_domains, esm_embeddings, included_substrates_file, + crossval_dir_bacterial) + else: + + test_parasect_esm(session, model, bacterial_domains, included_substrates_file, esm_embeddings, + crossval_dir_bacterial, hashes, n_components=n_components) if __name__ == "__main__": @@ -126,4 +185,5 @@ def do_crossvalidation(session: Session, crossvalidation_folder: str, out_dir: s engine = create_engine(f"sqlite:///{args.database}") with Session(engine) as session: - do_crossvalidation(session, args.crossval_folder, args.output, args.esm_pca) \ No newline at end of file + do_crossvalidation(session, args.crossval_folder, args.output, args.esm_pca, + args.parasect, args.bitvector_size, args.n_components) \ No newline at end of file diff --git a/src/parasect/model_training/rf/test_rf.py b/src/parasect/model_training/rf/test_rf.py index d7e1678..3bb2069 100644 --- a/src/parasect/model_training/rf/test_rf.py +++ b/src/parasect/model_training/rf/test_rf.py @@ -1,15 +1,65 @@ import os +from typing import Any, Optional +from statistics import mean, stdev from sklearn.ensemble import RandomForestClassifier import numpy as np -from numpy.typing import NDArray -from parasect.database.build_database import AdenylationDomain +from sqlalchemy.orm import Session + +from parasect.core.chem import fingerprint_to_bitvector +from parasect.database.query_database import get_substrates_from_name +from parasect.database.build_database import AdenylationDomain, Substrate from parasect.core.parsing import parse_list, parse_pcs from parasect.core.featurisation import get_domain_features from parasect.model_training.data_processing.plotting.confusion_matrix import plot_matrix, write_matrix +def write_parasect_metrics(tp, tp_probs, fp, fp_probs, tn, tn_probs, fn, fn_probs, + correct_ranks, incorrect_ranks, substrate_metrics, out_file): + with open(out_file, 'w') as out: + out.write("substrate\tprecision\trecall\tf1\tmean_rank_correct\tsd_rank_correct\tmean_rank_incorrect\tsd_rank_incorrect\ttp\tmean_prob_tp\tsd_prob_tp\tfp\tmean_prob_fp\tsd_prob_fp\tfn\tmean_prob_fn\tsd_prob_fn\ttn\tmean_prob_tn\tsd_prob_tn\n") + eps = 1e-9 + + + + precision = tp / (tp + fp) if (tp + fp) > eps else "N/A" + recall = tp / (tp + fn) if (tp + fn) > eps else "N/A" + + print(f"Overall precision: {precision}") + print(f"Overall recall: {recall}") + + f1 = 2 * (precision * recall) / (precision + recall) if (precision != 'N/A' and recall != 'N/A' and precision + recall > eps) else 'N/A' + tp_prob, tp_prob_sd = get_mean_stdev(tp_probs) + fp_prob, fp_prob_sd = get_mean_stdev(fp_probs) + tn_prob, tn_prob_sd = get_mean_stdev(tn_probs) + fn_prob, fn_prob_sd = get_mean_stdev(fn_probs) + rank_correct, rank_correct_sd = get_mean_stdev(correct_ranks) + rank_incorrect, rank_incorrect_sd = get_mean_stdev(incorrect_ranks) + + out.write(f"all\t{precision}\t{recall}\t{f1}\t{rank_correct}\t{rank_correct_sd}\t{rank_incorrect}\t{rank_incorrect_sd}\t{tp}\t{tp_prob}\t{tp_prob_sd}\t{fp}\t{fp_prob}\t{fp_prob_sd}\t{fn}\t{fn_prob}\t{fn_prob_sd}\t{tn}\t{tn_prob}\t{tn_prob_sd}\n") + for substrate, metrics in substrate_metrics.items(): + tp = metrics["TP"] + fp = metrics["FP"] + tn = metrics["TN"] + fn = metrics["FN"] + + precision = tp / (tp + fp) if (tp + fp) > eps else "N/A" + recall = tp / (tp + fn) if (tp + fn) > eps else "N/A" + f1 = 2 * (precision * recall) / (precision + recall) if (precision != 'N/A' and recall != 'N/A' and precision + recall > eps) else 'N/A' + + tp_prob, tp_prob_sd = get_mean_stdev(metrics["TP probabilities"]) + fp_prob, fp_prob_sd = get_mean_stdev(metrics["FP probabilities"]) + tn_prob, tn_prob_sd = get_mean_stdev(metrics["TN probabilities"]) + fn_prob, fn_prob_sd = get_mean_stdev(metrics["FN probabilities"]) + + rank_correct, rank_correct_sd = get_mean_stdev(metrics["correct_ranks"]) + rank_incorrect, rank_incorrect_sd = get_mean_stdev(metrics["incorrect_ranks"]) + + out.write( + f"{substrate.name}\t{precision}\t{recall}\t{f1}\t{rank_correct}\t{rank_correct_sd}\t{rank_incorrect}\t{rank_incorrect_sd}\t{tp}\t{tp_prob}\t{tp_prob_sd}\t{fp}\t{fp_prob}\t{fp_prob_sd}\t{fn}\t{fn_prob}\t{fn_prob_sd}\t{tn}\t{tn_prob}\t{tn_prob_sd}\n") + + def write_accuracy(overall_accuracy, per_substrate_accuracy, out_file): with open(out_file, 'w') as out: out.write(f"substrate\taccuracy\n") @@ -23,10 +73,165 @@ def write_accuracy(overall_accuracy, per_substrate_accuracy, out_file): out.write(f"{substrate}\tN/A\n") +def get_mean_stdev(list_of_values): + if len(list_of_values) > 0: + mean_value = mean(list_of_values) + if len(list_of_values) > 1: + stdev_value = stdev(list_of_values) + else: + stdev_value = "N/A" + else: + mean_value = "N/A" + stdev_value = "N/A" + + return mean_value, stdev_value + + +def fmt(val): + return f"{val:.3f}" if isinstance(val, (float, int)) else str(val) + + +def write_confidences(correct_confidences, incorrect_confidences, per_substrate_confidences, out_file): + with open(out_file, 'w') as out: + out.write(f"substrate\tconfidence_correct\tstdev_correct\tconfidence_incorrect\tstdev_incorrect\n") + mean_correct, stdev_correct = get_mean_stdev(correct_confidences) + mean_incorrect, stdev_incorrect = get_mean_stdev(incorrect_confidences) + + out.write( + f"all\t{fmt(mean_correct)}\t{fmt(stdev_correct)}\t{fmt(mean_incorrect)}\t{fmt(stdev_incorrect)}\n" + ) + substrates = sorted(per_substrate_confidences.keys()) + for substrate in substrates: + substrate_mean_correct, substrate_stdev_correct = get_mean_stdev( + per_substrate_confidences[substrate]["correct"]) + substrate_mean_incorrect, substrate_stdev_incorrect = get_mean_stdev( + per_substrate_confidences[substrate]["incorrect"]) + + out.write( + f"{substrate}\t{fmt(substrate_mean_correct)}\t{fmt(substrate_stdev_correct)}\t" + f"{fmt(substrate_mean_incorrect)}\t{fmt(substrate_stdev_incorrect)}\n" + ) + +def test_parasect_esm(session: Session, classifier: RandomForestClassifier, + domains: list[AdenylationDomain], + included_substrates_file: str, + embeddings_file: str, + out_dir: str, + hashes: list[int], + n_components: int = 100) -> None: + """Test PARASECT RF trained on ESM PCA + + :param session: database session + :type session: Session + :param classifier: PARASECT classifier + :type classifier: RandomForestClassifier + :param domains: list of adenylation domains to test + :type domains: list[AdenylationDomain] + :param included_substrates_file: path to file containing included substrates + :type included_substrates_file: str + :param embeddings_file: + :type embeddings_file: + :param out_dir: path to output directory + :type out_dir: str + :param hashes: list of hashes representing substrates used for training PARASECT model + :type hashes: list[int] + :param n_components: + :type n_components: + """ + included_substrate_names = parse_list(included_substrates_file) + + included_substrates = [] + substrates_to_predictions = {} + + domains_pca, pca_data = parse_pcs(embeddings_file) + domain_to_pcs = { + domain: pca_data[i][:n_components] + for i, domain in enumerate(domains_pca)} + + for name in included_substrate_names: + included_substrates.append(get_substrates_from_name(session, name)[0]) + + for substrate in included_substrates: + features = [] + for domain in domains: + domain_features = domain_to_pcs[domain.get_name()] + substrate_features = fingerprint_to_bitvector(hashes, set(substrate.fingerprint)) + features.append(np.array(list(domain_features) + list(substrate_features))) + + features = np.array(features) + + predict_y = classifier.predict_proba(features) + + predictions = [] + for prediction in predict_y: + + prob_per_class = list(zip(prediction, classifier.classes_)) + for prob, cls in prob_per_class: + if cls == 1: + predictions.append(prob) + + substrates_to_predictions[substrate] = predictions + + write_predictions_parasect(domains, substrates_to_predictions, out_dir) + + +def test_parasect_signatures(session: Session, classifier: RandomForestClassifier, + domains: list[AdenylationDomain], + included_substrates_file: str, + out_dir: str, + hashes: list[int]) -> None: + """Test PARASECT RF trained on signatures + + :param session: database session + :type session: Session + :param classifier: PARASECT classifier + :type classifier: RandomForestClassifier + :param domains: list of adenylation domains to test + :type domains: list[AdenylationDomain] + :param included_substrates_file: path to file containing included substrates + :type included_substrates_file: str + :param out_dir: path to output directory + :type out_dir: str + :param hashes: list of hashes representing substrates used for training PARASECT model + :type hashes: list[int] + """ + + included_substrate_names = parse_list(included_substrates_file) + + included_substrates = [] + substrates_to_predictions = {} + for name in included_substrate_names: + included_substrates.append(get_substrates_from_name(session, name)[0]) + + for substrate in included_substrates: + features = [] + for domain in domains: + + domain_features = get_domain_features(domain.extended_signature) + substrate_features = fingerprint_to_bitvector(hashes, set(substrate.fingerprint)) + features.append(np.array(domain_features + substrate_features)) + + features = np.array(features) + + predict_y = classifier.predict_proba(features) + + predictions = [] + for prediction in predict_y: + + prob_per_class = list(zip(prediction, classifier.classes_)) + for prob, cls in prob_per_class: + if cls == 1: + predictions.append(prob) + + substrates_to_predictions[substrate] = predictions + + write_predictions_parasect(domains, substrates_to_predictions, out_dir) + + def test_paras_signatures(classifier: RandomForestClassifier, domains: list[AdenylationDomain], included_substrates_file: str, out_dir: str) -> None: - """Test RF trained on PARAS signatures + """Test PARAS RF trained on signatures :param classifier: random forest classifier :type classifier: RandomForestClassifier @@ -37,19 +242,26 @@ def test_paras_signatures(classifier: RandomForestClassifier, :param out_dir: path to output directory :type out_dir: str """ - if not os.path.exists(out_dir): - os.mkdir(out_dir) features = np.array([get_domain_features(domain.extended_signature) for domain in domains]) - predictions = classifier.predict(features) + predict_y = classifier.predict_proba(features) - write_predictions(domains, predictions, included_substrates_file, out_dir) + + predictions = [] + for prediction in predict_y: + prob_per_class = list(zip(prediction, classifier.classes_)) + + prob_per_class.sort(reverse=True) + predictions.append(prob_per_class) + + write_predictions_paras(domains, predictions, included_substrates_file, out_dir) def test_paras_esm(classifier: RandomForestClassifier, domains: list[AdenylationDomain], - embeddings_file: str, included_substrates_file: str, out_dir: str) -> None: - """Test RF trained on PARAS signatures + embeddings_file: str, included_substrates_file: str, out_dir: str, + n_components: int = 100) -> None: + """Test PARAS RF trained on ESM PCA embeddings :param classifier: random forest classifier :type classifier: RandomForestClassifier @@ -62,46 +274,65 @@ def test_paras_esm(classifier: RandomForestClassifier, :param out_dir: path to output directory :type out_dir: str """ - if not os.path.exists(out_dir): - os.mkdir(out_dir) domains_pca, pca_data = parse_pcs(embeddings_file) name_to_row = {name: row for name, row in zip(domains_pca, pca_data)} - features = np.array([name_to_row[d.get_name()] for d in domains]) + features = np.array([name_to_row[d.get_name()][:n_components] for d in domains]) - predictions = classifier.predict(features) - write_predictions(domains, predictions, included_substrates_file, out_dir) + predict_y = classifier.predict_proba(features) + predictions = [] + for prediction in predict_y: + prob_per_class = list(zip(prediction, classifier.classes_)) -def write_predictions(domains: list[AdenylationDomain], predictions: NDArray[np.str_], - included_substrates_file: str, - out_dir: str): + prob_per_class.sort(reverse=True) + predictions.append(prob_per_class) + + write_predictions_paras(domains, predictions, included_substrates_file, out_dir) + + +def write_predictions_paras(domains: list[AdenylationDomain], predictions: list, + included_substrates_file: str, + out_dir: str): """Write predictions to output directory :param domains: list of adenylation domains :type domains: list[AdenylationDomain] :param predictions: predictions made by classifier - :type predictions: NDArray[np.str_] + :type predictions: NDArray :param included_substrates_file: path to file containing included substrates :type included_substrates_file: str :param out_dir: path to output directory :type out_dir: str """ + if not os.path.exists(out_dir): + os.mkdir(out_dir) + + print("Writing files...") + overall_correct = 0 overall_incorrect = 0 per_substrate_counts = {} # {substrate_name: [correct, total]} + per_substrate_confidences = {} included_substrate_names = parse_list(included_substrates_file) for substrate in included_substrate_names: per_substrate_counts[substrate] = [0, 0] + per_substrate_confidences[substrate] = {"correct": [], + "incorrect": []} substrate_nr = len(included_substrate_names) confusion_matrix = np.zeros(shape=(substrate_nr, substrate_nr)) - for i, prediction in enumerate(predictions): + correct_confidences = [] + incorrect_confidences = [] + + for i, prediction_matrix in enumerate(predictions): + prediction = prediction_matrix[0][1] + confidence = prediction_matrix[0][0] prediction_index = included_substrate_names.index(prediction) substrate_names = [s.name for s in domains[i].substrates] substrate_index = None @@ -115,14 +346,19 @@ def write_predictions(domains: list[AdenylationDomain], predictions: NDArray[np. if prediction in substrate_names: overall_correct += 1 + correct_confidences.append(confidence) + per_substrate_confidences[prediction]["correct"].append(confidence) else: overall_incorrect += 1 + incorrect_confidences.append(confidence) + per_substrate_confidences[prediction]["incorrect"].append(confidence) for substrate in substrate_names: if substrate in included_substrate_names: per_substrate_counts[substrate][1] += 1 # total if prediction == substrate: per_substrate_counts[substrate][0] += 1 # correct + break # Compute accuracies overall_accuracy = overall_correct / (overall_correct + overall_incorrect) @@ -134,9 +370,144 @@ def write_predictions(domains: list[AdenylationDomain], predictions: NDArray[np. out_plot = os.path.join(out_dir, "confusion_matrix.svg") out_matrix = os.path.join(out_dir, "confusion_matrix.txt") - out_accuracy = os.path.join(out_dir, "metrics.txt") + out_accuracy = os.path.join(out_dir, "accuracy.txt") + out_confidence = os.path.join(out_dir, "confidence.txt") plot_matrix(confusion_matrix, included_substrate_names, out_plot) write_matrix(confusion_matrix, included_substrate_names, out_matrix) - + write_confidences(correct_confidences, incorrect_confidences, per_substrate_confidences, out_confidence) write_accuracy(overall_accuracy, per_substrate_accuracy, out_accuracy) + + +def reverse_rank(values: list[float], idx: int) -> int: + """ + Compute 1-indexed reverse rank of element at index `idx` in `values`. + Largest value gets rank 1. + """ + target = values[idx] + # Count how many elements are strictly greater than target + rank = sum(v > target for v in values) + 1 + return rank + + +def write_predictions_parasect(domains: list[AdenylationDomain], substrate_to_predictions: dict[Substrate, list], + out_dir: str): + if not os.path.exists(out_dir): + os.mkdir(out_dir) + + print("Writing files..") + + substrate_to_metrics: dict[Substrate, dict[str, Any]] = {} + substrate_nr = len(substrate_to_predictions) + confusion_matrix = np.zeros(shape=(substrate_nr, substrate_nr)) + domain_to_best_prob: dict[AdenylationDomain, float] = {} + domain_to_best: dict[AdenylationDomain, Optional[Substrate]] = {} + domain_to_probs: dict[AdenylationDomain, dict[str, list[float]]] = {} + domain_to_predictions: dict[AdenylationDomain, list[float]] = {} + for domain in domains: + domain_to_best_prob[domain] = 0.0 + domain_to_best[domain] = None + domain_to_probs[domain] = {"correct": [], + "incorrect": []} + domain_to_predictions[domain] = [] + + substrates = sorted(substrate_to_predictions.keys()) + + for substrate in substrates: + predictions = substrate_to_predictions[substrate] + substrate_to_metrics[substrate] = {"TP": 0, + "FP": 0, + "TN": 0, + "FN": 0, + "TP probabilities": [], + "FP probabilities": [], + "TN probabilities": [], + "FN probabilities": [], + "correct_ranks": [], + "incorrect_ranks": [] + } + + for i, interaction_probability in enumerate(predictions): + domain = domains[i] + domain_to_predictions[domain].append(interaction_probability) + if interaction_probability > domain_to_best_prob[domain]: + domain_to_best[domain] = substrate + domain_to_best_prob[domain] = interaction_probability + if substrate in domain.substrates: + domain_to_probs[domain]["correct"].append(interaction_probability) + else: + domain_to_probs[domain]["incorrect"].append(interaction_probability) + + correct_ranks = [] + incorrect_ranks = [] + + tp = 0 + fp = 0 + fn = 0 + tn = 0 + + tp_probs = [] + fp_probs = [] + fn_probs = [] + tn_probs = [] + + for i, domain in enumerate(domains): + + for j, substrate in enumerate(substrates): + + rank = reverse_rank(list(domain_to_predictions[domain]), j) + if substrate in domain.substrates: + substrate_to_metrics[substrate]["correct_ranks"].append(rank) + correct_ranks.append(rank) + else: + substrate_to_metrics[substrate]["incorrect_ranks"].append(rank) + incorrect_ranks.append(rank) + + best_prediction = domain_to_best[domain] + prediction_index = substrates.index(best_prediction) + substrate_index = None + for substrate in domain.substrates: + if substrate in substrates: + substrate_index = substrates.index(substrate) + break + + if substrate_index is not None: + confusion_matrix[prediction_index][substrate_index] += 1 + if best_prediction in domain.substrates: + substrate_to_metrics[best_prediction]["TP"] += 1 + substrate_to_metrics[best_prediction]["TP probabilities"].append(domain_to_best_prob[domain]) + tp += 1 + tp_probs.append(domain_to_best_prob[domain]) + for substrate in substrate_to_predictions: + if substrate not in domain.substrates: + substrate_to_metrics[substrate]["TN"] += 1 + interaction_probability = substrate_to_predictions[substrate][i] + substrate_to_metrics[best_prediction]["TN probabilities"].append(interaction_probability) + tn += 1 + tn_probs.append(interaction_probability) + + else: + substrate_to_metrics[best_prediction]["FP"] += 1 + substrate_to_metrics[best_prediction]["FP probabilities"].append(domain_to_best_prob[domain]) + fp += 1 + fp_probs.append(domain_to_best_prob[domain]) + + for substrate in domain.substrates: + if substrate in substrates: + substrate_to_metrics[substrate]["FN"] += 1 + interaction_probability = substrate_to_predictions[substrate][i] + substrate_to_metrics[best_prediction]["FN probabilities"].append(interaction_probability) + fn += 1 + fn_probs.append(interaction_probability) + + out_file = os.path.join(out_dir, "parasect_performance.txt") + + write_parasect_metrics(tp, tp_probs, fp, fp_probs, tn, tn_probs, fn, fn_probs, correct_ranks, incorrect_ranks, + substrate_to_metrics, out_file) + + out_plot = os.path.join(out_dir, "confusion_matrix.svg") + out_matrix = os.path.join(out_dir, "confusion_matrix.txt") + + + plot_matrix(confusion_matrix, substrates, out_plot) + write_matrix(confusion_matrix, [s.name for s in substrates], out_matrix) diff --git a/src/parasect/model_training/rf/train_rf.py b/src/parasect/model_training/rf/train_rf.py index 1466556..bdd20ef 100644 --- a/src/parasect/model_training/rf/train_rf.py +++ b/src/parasect/model_training/rf/train_rf.py @@ -1,18 +1,60 @@ from typing import Optional - +from argparse import ArgumentParser, Namespace from joblib import dump from numpy.typing import NDArray import numpy as np from sklearn.ensemble import RandomForestClassifier from sqlalchemy.orm import Session +from sqlalchemy import create_engine from imblearn.under_sampling import RandomUnderSampler +import os from parasect.core.chem import get_fingerprint_hashes, fingerprint_to_bitvector from parasect.core.featurisation import get_domain_features +from parasect.core.writers import write_list + from parasect.database.query_database import get_domains_from_synonym, get_substrates_from_name from parasect.core.parsing import parse_list, parse_pcs from parasect.model_training.train_test_splits.substrate_selection import SubstrateSelectionMode, \ map_domains_to_substrates +from parasect.model_training.train_test_splits.domain_scope import DomainScope +from parasect.model_training.rf.test_rf import test_paras_signatures, test_paras_esm, \ + test_parasect_signatures, test_parasect_esm +from parasect.database.flatfiles_from_db import write_domain_names, write_substrate_names + + +def parse_arguments() -> Namespace: + """Parse arguments from command line + + :return: Arguments + :rtype: Namespace + """ + parser = ArgumentParser(description="Split domains into train and test set based on taxonomy") + + parser.add_argument("-db", "--database", type=str, required=True, + help="Path to PARASECT database") + parser.add_argument("-o", "--out", required=True, type=str, + help="Output directory") + parser.add_argument("-e", "--esm_embeddings", type=str, default=None, + help="Path to PCA of ESM embeddings. If given, train in ESM PCA embedding mode") + parser.add_argument("-p", "--parasect", action="store_true", + help="If given, do crossvalidation for PARASECT models instead of PARAS models") + parser.add_argument("-n", "--n_components", type=int, default=100, + help="Number of ESM principal components to use for domain featurisation") + parser.add_argument('-b', "--bitvector_size", type=int, default=1024, + help="Size of ECFP4 bitvectors for substrate featurisation") + parser.add_argument('-train', "--train", default=None, + help="List of domains to train on. If not given, train on all domains") + parser.add_argument('-s', '--selection_mode', default="FIRST_ONLY", + help="Substrate selection mode for determining substrate labels") + parser.add_argument("-i", "--included_substrates", default=None, type=str, + help="File containing list of included substrates. If not given, use all substrates") + parser.add_argument('-test', "--test", default=None, + help="If given, test model on this domain list and write results to output folder") + + args = parser.parse_args() + + return args def train_random_forest(features: NDArray[np.float64], labels: NDArray[np.str], @@ -42,7 +84,7 @@ def train_random_forest(features: NDArray[np.float64], labels: NDArray[np.str], def train_paras_esm(session: Session, domain_list: str, selection_mode: SubstrateSelectionMode, - included_substrates_file: str, pca_file: str, + included_substrates_file: str, pca_file: str, n_components: int = 100, out_path: Optional[str] = None) -> RandomForestClassifier: """ @@ -56,6 +98,8 @@ def train_paras_esm(session: Session, domain_list: str, selection_mode: Substrat :type domain_list: str :param pca_file: path to file containing pca of esm embeddings :type pca_file: str + :param n_components: number of principal components to use as features + :type n_components: int :param out_path: if given, save model to out path :type out_path: Optional[str @@ -64,7 +108,7 @@ def train_paras_esm(session: Session, domain_list: str, selection_mode: Substrat domains_pca, pca_data = parse_pcs(pca_file) domain_to_pcs = { - domain: pca_data[i] + domain: pca_data[i][:n_components] for i, domain in enumerate(domains_pca) if domain in domain_names } @@ -91,6 +135,8 @@ def train_paras_esm(session: Session, domain_list: str, selection_mode: Substrat features = np.array([domain_to_pcs[domain.get_name()] for domain in domains]) labels = np.array([domain_to_substrate[domain].name for domain in domains]) + print("Training PARAS classifier...") + classifier = train_random_forest(features, labels, out_path=out_path) return classifier @@ -98,7 +144,7 @@ def train_paras_esm(session: Session, domain_list: str, selection_mode: Substrat def train_parasect_signatures(session: Session, domain_list: str, included_substrates_file: str, - bitvector_size: int = 256, + bitvector_size: int = 1024, out_path: Optional[str] = None) -> tuple[RandomForestClassifier, list[int]]: """Train PARASECT on extended signatures @@ -154,8 +200,12 @@ def train_parasect_signatures(session: Session, domain_list: str, undersampler = RandomUnderSampler(random_state=25051989) + print("Sampling...") + features, labels = undersampler.fit_resample(train_x, train_y) + print("Training PARASECT classifier...") + classifier = train_random_forest(features, labels, out_path=out_path) return classifier, hashes @@ -164,6 +214,7 @@ def train_parasect_signatures(session: Session, domain_list: str, def train_parasect_esm(session: Session, domain_list: str, included_substrates_file: str, pca_file: str, + n_components: int = 100, bitvector_size: int = 256, out_path: Optional[str] = None) -> tuple[RandomForestClassifier, list[int]]: """Train PARASECT on ESM features @@ -174,6 +225,8 @@ def train_parasect_esm(session: Session, domain_list: str, :type included_substrates_file: str :param pca_file: path to pca file :type pca_file: str + :param n_components: number of principal components to use for model training + :type n_components: int :param bitvector_size: size of bitvector :type bitvector_size: int :param domain_list: file path containing list of domains to train on @@ -189,7 +242,7 @@ def train_parasect_esm(session: Session, domain_list: str, domains_pca, pca_data = parse_pcs(pca_file) domain_to_pcs = { - domain: pca_data[i] + domain: pca_data[i][:n_components] for i, domain in enumerate(domains_pca) if domain in domain_names } @@ -222,7 +275,7 @@ def train_parasect_esm(session: Session, domain_list: str, for substrate in included_substrates: domain_features = domain_to_pcs[domain.get_name()] substrate_features = fingerprint_to_bitvector(hashes, set(substrate.fingerprint)) - train_x.append(np.array(domain_features + substrate_features)) + train_x.append(np.array(list(domain_features) + list(substrate_features))) if substrate in domain_to_substrates[domain]: train_y.append(1) else: @@ -233,8 +286,12 @@ def train_parasect_esm(session: Session, domain_list: str, undersampler = RandomUnderSampler(random_state=25051989) + print("Sampling...") + features, labels = undersampler.fit_resample(train_x, train_y) + print("Training PARASECT classifier...") + classifier = train_random_forest(features, labels, out_path=out_path) return classifier, hashes @@ -286,6 +343,133 @@ def train_paras_signatures(session: Session, domain_list: str, features = np.array([get_domain_features(domain.extended_signature) for domain in domains]) labels = np.array([domain_to_substrate[domain].name for domain in domains]) + print("Training PARAS classifier...") + classifier = train_random_forest(features, labels, out_path=out_path) return classifier + + +def main(): + args = parse_arguments() + + selection_mode = SubstrateSelectionMode[args.selection_mode.upper()] + + engine = create_engine(f"sqlite:///{args.database}") + if not os.path.exists(args.out): + os.mkdir(args.out) + + if args.parasect: + model_path = os.path.join(args.out, "model.parasect") + else: + model_path = os.path.join(args.out, "model.paras") + + with Session(engine) as session: + + train_file = os.path.join(args.out, "train_domains.txt") + if args.train is None: + write_domain_names(session, train_file) + else: + write_list(parse_list(args.train), train_file) + + included_substrates_file = os.path.join(args.out, "included_substrates.txt") + if args.included_substrates is None: + write_substrate_names(session, included_substrates_file) + else: + write_list(parse_list(args.included_substrates), included_substrates_file) + + hashes = [] + if args.esm_embeddings is None: + if not args.parasect: + model = train_paras_signatures(session, train_file, selection_mode, + included_substrates_file, out_path=model_path) + else: + model, hashes = train_parasect_signatures(session, train_file, included_substrates_file, + args.bitvector_size, out_path=model_path) + + print(f"Number of hashes: {len(hashes)}") + else: + if not args.parasect: + model = train_paras_esm(session, train_file, selection_mode, + included_substrates_file, + args.esm_embeddings, args.n_components, out_path=model_path) + else: + model, hashes = train_parasect_esm(session, train_file, included_substrates_file, args.esm_embeddings, + args.n_components, args.bitvector_size, out_path=model_path) + + print(f"Number of hashes: {len(hashes)}") + + if hashes: + write_list(hashes, os.path.join(args.out, "hashes.txt"), sort=False) + + if args.test: + test_dir = os.path.join(args.out, f"test_all") + test_dir_fungal = os.path.join(args.out, f"test_fungal") + test_dir_bacterial = os.path.join(args.out, f"test_bacterial") + + domain_names = parse_list(args.test) + domains = [] + write_list(domain_names, os.path.join(args.out, "test.txt")) + for domain in domain_names: + synonym = domain.split('|')[0] + domains.append(get_domains_from_synonym(session, synonym)[0]) + + fungal_domains = list(set(DomainScope.get_domains(session, DomainScope.FUNGAL_ONLY)).intersection(set(domains))) + bacterial_domains = list( + set(DomainScope.get_domains(session, DomainScope.BACTERIAL_ONLY)).intersection(set(domains))) + + print(f"\nTesting all domains...") + + if args.esm_embeddings is None: + if not args.parasect: + test_paras_signatures(model, domains, included_substrates_file, test_dir) + else: + assert selection_mode == SubstrateSelectionMode.ALL + test_parasect_signatures(session, model, domains, included_substrates_file, test_dir, hashes) + + else: + if not args.parasect: + test_paras_esm(model, domains, args.esm_embeddings, included_substrates_file, test_dir, + n_components=args.n_components) + else: + test_parasect_esm(session, model, domains, included_substrates_file, args.esm_embeddings, test_dir, + hashes, n_components=args.n_components) + + if fungal_domains and set(fungal_domains) != set(domains): + write_list([f.get_name() for f in fungal_domains], os.path.join(args.out, "fungal_test.txt")) + print(f"\nTesting fungal domains...") + if args.esm_embeddings is None: + if not args.parasect: + test_paras_signatures(model, fungal_domains, included_substrates_file, test_dir_fungal) + else: + test_parasect_signatures(session, model, fungal_domains, included_substrates_file, + test_dir_fungal, hashes) + else: + if not args.parasect: + test_paras_esm(model, fungal_domains, args.esm_embeddings, included_substrates_file, + test_dir_fungal) + else: + test_parasect_esm(session, model, fungal_domains, included_substrates_file, args.esm_embeddings, + test_dir_fungal, hashes, n_components=args.n_components) + if bacterial_domains and set(bacterial_domains) != set(domains): + write_list([b.get_name() for b in bacterial_domains], os.path.join(args.out, "bacterial_test.txt")) + print(f"\nTesting bacterial domains...") + if args.esm_embeddings is None: + if not args.parasect: + test_paras_signatures(model, bacterial_domains, included_substrates_file, test_dir_bacterial) + else: + test_parasect_signatures(session, model, bacterial_domains, included_substrates_file, + test_dir_bacterial, hashes) + else: + if not args.parasect: + test_paras_esm(model, bacterial_domains, args.esm_embeddings, included_substrates_file, + test_dir_bacterial) + else: + + test_parasect_esm(session, model, bacterial_domains, included_substrates_file, + args.esm_embeddings, + test_dir_bacterial, hashes, n_components=args.n_components) + + +if __name__ == "__main__": + main() From d9297e88e1338580f06da3ed75cf2a73bcca206a Mon Sep 17 00:00:00 2001 From: "Terlouw, Barbara" Date: Mon, 22 Sep 2025 15:52:20 +0200 Subject: [PATCH 53/65] Write fingerprints to file when training random forest --- src/parasect/model_training/rf/train_rf.py | 17 +++++++++++++++++ 1 file changed, 17 insertions(+) diff --git a/src/parasect/model_training/rf/train_rf.py b/src/parasect/model_training/rf/train_rf.py index bdd20ef..708d69f 100644 --- a/src/parasect/model_training/rf/train_rf.py +++ b/src/parasect/model_training/rf/train_rf.py @@ -401,6 +401,23 @@ def main(): if hashes: write_list(hashes, os.path.join(args.out, "hashes.txt"), sort=False) + fingerprints_file = os.path.join(args.out, "fingerprints.txt") + included_substrate_names = parse_list(included_substrates_file) + included_substrates = [] + for name in included_substrate_names: + included_substrates.append(get_substrates_from_name(session, name)[0]) + + with open(fingerprints_file, 'w') as fingerprints: + fingerprints.write("substrate_name\tsmiles") + for fp_hash in hashes: + fingerprints.write(f"\t{fp_hash}") + fingerprints.write('\n') + for substrate in included_substrates: + fingerprints.write(f"{substrate.name}\t{substrate.smiles}") + bitvector = fingerprint_to_bitvector(hashes, set(substrate.fingerprint)) + for value in bitvector: + fingerprints.write(f"\t{value}") + fingerprints.write('\n') if args.test: test_dir = os.path.join(args.out, f"test_all") From 81a4d0b5d889b8cc1eb7b6c4ff0a32d2b32abeab Mon Sep 17 00:00:00 2001 From: "Terlouw, Barbara" Date: Mon, 22 Sep 2025 15:52:47 +0200 Subject: [PATCH 54/65] Update fingerprints --- src/parasect/api.py | 9 +- src/parasect/data/fingerprints.txt | 297 ++++------------------------- 2 files changed, 42 insertions(+), 264 deletions(-) diff --git a/src/parasect/api.py b/src/parasect/api.py index 6421c49..73a4280 100644 --- a/src/parasect/api.py +++ b/src/parasect/api.py @@ -11,11 +11,8 @@ from parasect.core.domain import AdenylationDomain from parasect.database.build_database import AdenylationDomain as ADomain from parasect.core.featurisation import get_domain_features, get_domains -from parasect.core.parsing import ( - bitvector_from_smiles, - data_from_substrate_names, - parse_substrate_list, -) +from parasect.core.parsing import bitvector_from_smiles, data_from_substrate_names, parse_list + from parasect.core.genbank import fetch_from_genbank from parasect.core.tabular import Tabular from parasect.core.parasect_result import Result @@ -209,7 +206,7 @@ def run_parasect( :raises RuntimeError: If no feature vectors are found. """ # get names of included substrates - included_subs = parse_substrate_list(INCLUDED_SUBSTRATES_FILE) + included_subs = parse_list(INCLUDED_SUBSTRATES_FILE) # get smiles and fingerprints for the included substrates if not only_custom: diff --git a/src/parasect/data/fingerprints.txt b/src/parasect/data/fingerprints.txt index 76e291e..90c9065 100644 --- a/src/parasect/data/fingerprints.txt +++ b/src/parasect/data/fingerprints.txt @@ -1,258 +1,39 @@ -substrate_name smiles 3522799069 3977576644 829081502 2283234228 1258652603 2778693672 3883946894 458548175 1048241268 1315488206 3890940231 3785825467 1221344109 3759982330 1237514124 3538434540 3245598400 1902793822 3040137212 4204299438 1480508801 104167773 1792085364 117839297 1103368761 4045618653 1644387425 3102446724 1162798390 3129448451 1683408722 2693181564 1159568610 256887294 219781469 3349951008 2768932647 3456327963 3607054346 443815054 4087496155 2308377447 34462953 3224747051 265701480 416056630 510516219 268216641 2521443851 3732059725 380667285 391515775 732554456 915323707 501273492 2724517795 3470878254 1542250589 1465927948 4245461869 3000515102 789120837 2627830799 1120095700 3287910036 820078184 1775807013 4116211921 2599389977 2609627136 3323433943 880017916 1432881809 160964508 569011984 3899012600 1311937448 2873181291 1445199843 3496305263 3222860449 664602416 74969580 1655178002 1892122844 150823180 57331338 4270924184 1560482217 340599072 1081062448 1492400498 2878827962 4189253755 1489234848 1643338164 1615910677 1626128111 1560230541 191420530 302551299 4228513841 644496620 896684412 1308885986 319727467 2765655922 3357910814 730777171 1816371330 2846902980 857522858 854976359 2997081563 2526476749 3693226511 1448004819 316813980 2440705014 3979187671 2086678682 3382787824 3525688319 3968606436 3913635106 2675832621 297795514 1308055156 3513795428 3945718905 3435906257 3437611417 3278281630 1861380856 2256192740 1885701351 2801431730 2361362345 2905685841 770950994 1505419959 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0 0 0 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 From 58ce77a34160d24033f3eb20ad89f74fd735609b Mon Sep 17 00:00:00 2001 From: "Terlouw, Barbara" Date: Mon, 22 Sep 2025 15:53:26 +0200 Subject: [PATCH 55/65] Update models --- src/parasect/cli_paras.py | 4 ++-- src/parasect/cli_parasect.py | 2 +- src/parasect/data/included_substrates.txt | 6 +++++- 3 files changed, 8 insertions(+), 4 deletions(-) diff --git a/src/parasect/cli_paras.py b/src/parasect/cli_paras.py index 42c5a02..56598d2 100644 --- a/src/parasect/cli_paras.py +++ b/src/parasect/cli_paras.py @@ -68,11 +68,11 @@ def main() -> None: temp_dir = args.temp if args.all_substrates: - model_path = download_and_unpack_or_fetch(r"https://zenodo.org/records/13165500/files/all_substrates_model.paras?download=1", + model_path = download_and_unpack_or_fetch(r"https://zenodo.org/records/17155186/files/all_substrates_model.paras.gz?download=1", temp_dir, logger) else: - model_path = download_and_unpack_or_fetch(r"https://zenodo.org/records/13165500/files/model.paras?download=1", + model_path = download_and_unpack_or_fetch(r"https://zenodo.org/records/17155186/files/model.paras.gz?download=1", temp_dir, logger) model = load(model_path) diff --git a/src/parasect/cli_parasect.py b/src/parasect/cli_parasect.py index f238ec7..0c64f76 100644 --- a/src/parasect/cli_parasect.py +++ b/src/parasect/cli_parasect.py @@ -86,7 +86,7 @@ def main() -> None: raise ValueError("No substrates to test! Either include standard substrates or pass custom substrate SMILES") model_path = download_and_unpack_or_fetch( - r"https://zenodo.org/records/13165500/files/model.parasect?download=1", + r"https://zenodo.org/records/17155186/files/model.parasect.gz?download=1", temp_dir, logger) model = load(model_path) diff --git a/src/parasect/data/included_substrates.txt b/src/parasect/data/included_substrates.txt index cbd0348..e357460 100644 --- a/src/parasect/data/included_substrates.txt +++ b/src/parasect/data/included_substrates.txt @@ -1,10 +1,13 @@ +2,3-diaminopropionic acid 2,3-dihydroxybenzoic acid 2,4-diaminobutyric acid 2-aminoadipic acid 2-aminoisobutyric acid 3,5-dihydroxyphenylglycine 4-hydroxyphenylglycine +4R-hydroxyproline D-alanine +N5-acetyl-N5-hydroxyornithine N5-formyl-N5-hydroxyornithine N5-hydroxyornithine R-beta-hydroxytyrosine @@ -13,12 +16,14 @@ anthranilic acid arginine asparagine aspartic acid +benzoic acid beta-alanine cysteine glutamic acid glutamine glycine histidine +homoserine isoleucine leucine lysine @@ -26,7 +31,6 @@ ornithine phenylalanine pipecolic acid proline -salicylic acid serine threonine tryptophan From c2ea1253a296bb1beab781f8aec648044f8dfa58 Mon Sep 17 00:00:00 2001 From: "Terlouw, Barbara" Date: Mon, 22 Sep 2025 15:55:40 +0200 Subject: [PATCH 56/65] Update setup.cfg --- setup.cfg | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/setup.cfg b/setup.cfg index 11e213d..aa8aff8 100644 --- a/setup.cfg +++ b/setup.cfg @@ -46,7 +46,7 @@ install_requires = ncbi-acc-download>=0.2.5 sqlalchemy iterative-stratification==0.1.9 - imblearn==0.12.4 + imblearn pandas seaborn From b1b93968835803e04353ec2943734572e5a9b24c Mon Sep 17 00:00:00 2001 From: "Terlouw, Barbara" Date: Mon, 22 Sep 2025 15:56:27 +0200 Subject: [PATCH 57/65] Add init to model training module --- src/parasect/model_training/__init__.py | 0 1 file changed, 0 insertions(+), 0 deletions(-) create mode 100644 src/parasect/model_training/__init__.py diff --git a/src/parasect/model_training/__init__.py b/src/parasect/model_training/__init__.py new file mode 100644 index 0000000..e69de29 From f6a36b82ac228106eb96fc78413261780050023d Mon Sep 17 00:00:00 2001 From: "Terlouw, Barbara" Date: Mon, 22 Sep 2025 20:38:29 +0200 Subject: [PATCH 58/65] Bugfix: Add hmm binaries to parasect package data --- setup.cfg | 1 + 1 file changed, 1 insertion(+) diff --git a/setup.cfg b/setup.cfg index aa8aff8..841ffbc 100644 --- a/setup.cfg +++ b/setup.cfg @@ -67,6 +67,7 @@ where = src parasect.data = *.txt *.hmm + *.hmm.* *.tsv *.fasta From 04485688ec9edd6363b697c460f26b4e0272e14d Mon Sep 17 00:00:00 2001 From: "Terlouw, Barbara" Date: Mon, 29 Sep 2025 14:04:54 +0200 Subject: [PATCH 59/65] Add bacterial PARASECT model --- src/parasect/api.py | 22 ++++- src/parasect/cli_paras.py | 4 +- src/parasect/cli_parasect.py | 17 +++- src/parasect/core/chem.py | 24 ++++- src/parasect/core/constants.py | 2 + src/parasect/core/parsing.py | 14 ++- src/parasect/data/fingerprints_bacterial.txt | 31 ++++++ .../data/included_substrates_bacterial.txt | 30 ++++++ src/parasect/database/flatfiles_from_db.py | 94 ++++++++++++++++++- 9 files changed, 215 insertions(+), 23 deletions(-) create mode 100644 src/parasect/data/fingerprints_bacterial.txt create mode 100644 src/parasect/data/included_substrates_bacterial.txt diff --git a/src/parasect/api.py b/src/parasect/api.py index 73a4280..769ee6b 100644 --- a/src/parasect/api.py +++ b/src/parasect/api.py @@ -7,11 +7,12 @@ from sklearn.ensemble import RandomForestClassifier -from parasect.core.constants import FINGERPRINTS_FILE, INCLUDED_SUBSTRATES_FILE, SMILES_FILE +from parasect.core.constants import FINGERPRINTS_FILE, INCLUDED_SUBSTRATES_FILE, SMILES_FILE, \ + INCLUDED_SUBSTRATES_FILE_BACTERIAL, BACTERIAL_FINGERPRINTS_FILE from parasect.core.domain import AdenylationDomain from parasect.database.build_database import AdenylationDomain as ADomain from parasect.core.featurisation import get_domain_features, get_domains -from parasect.core.parsing import bitvector_from_smiles, data_from_substrate_names, parse_list +from parasect.core.parsing import bitvector_from_smiles, data_from_substrate_names, parse_substrate_list from parasect.core.genbank import fetch_from_genbank from parasect.core.tabular import Tabular @@ -181,6 +182,7 @@ def run_parasect( custom_substrate_smiles: Optional[List[str]] = None, only_custom: bool = False, use_structure_guided_alignment: bool = False, + bacterial_only: bool = False ) -> List[Result]: """Predict adenylation domain substrate specificity with PARASECT on raw input. @@ -200,17 +202,27 @@ def run_parasect( :type only_custom: bool :param use_structure_guided_alignment: Use structure guided alignment. :type use_structure_guided_alignment: bool + :param bacterial_only: Use bacterial model + :type bacterial_only: bool :return: Results. :rtype: List[Result] :raises ValueError: If substrate names, smiles, and fingerprints are not of the same length. :raises RuntimeError: If no feature vectors are found. """ # get names of included substrates - included_subs = parse_list(INCLUDED_SUBSTRATES_FILE) + if bacterial_only: + substrates_file = INCLUDED_SUBSTRATES_FILE_BACTERIAL + fingerprints_file = BACTERIAL_FINGERPRINTS_FILE + else: + substrates_file = INCLUDED_SUBSTRATES_FILE + fingerprints_file = FINGERPRINTS_FILE + + included_subs = parse_substrate_list(substrates_file) # get smiles and fingerprints for the included substrates if not only_custom: - sub_names, sub_smiles, sub_fps = data_from_substrate_names(included_subs) + + sub_names, sub_smiles, sub_fps = data_from_substrate_names(included_subs, bacterial_only=bacterial_only) else: sub_names, sub_smiles, sub_fps = [], [], [] @@ -225,7 +237,7 @@ def run_parasect( for custom_name, custom_smiles in zip(custom_substrate_names, custom_substrate_smiles): # get substrate fingerprints - custom_fp = bitvector_from_smiles(custom_smiles, FINGERPRINTS_FILE) + custom_fp = bitvector_from_smiles(custom_smiles, fingerprints_file) # add custom data to the included data sub_names.append(custom_name) diff --git a/src/parasect/cli_paras.py b/src/parasect/cli_paras.py index 56598d2..82af22e 100644 --- a/src/parasect/cli_paras.py +++ b/src/parasect/cli_paras.py @@ -68,11 +68,11 @@ def main() -> None: temp_dir = args.temp if args.all_substrates: - model_path = download_and_unpack_or_fetch(r"https://zenodo.org/records/17155186/files/all_substrates_model.paras.gz?download=1", + model_path = download_and_unpack_or_fetch(r"https://zenodo.org/records/17224548/files/all_substrates_model.paras.gz?download=1", temp_dir, logger) else: - model_path = download_and_unpack_or_fetch(r"https://zenodo.org/records/17155186/files/model.paras.gz?download=1", + model_path = download_and_unpack_or_fetch(r"https://zenodo.org/records/17224548/files/model.paras.gz?download=1", temp_dir, logger) model = load(model_path) diff --git a/src/parasect/cli_parasect.py b/src/parasect/cli_parasect.py index 0c64f76..941e4ec 100644 --- a/src/parasect/cli_parasect.py +++ b/src/parasect/cli_parasect.py @@ -40,6 +40,8 @@ def cli() -> argparse.Namespace: help="Save short 10 amino acid signatures to file ('Stachelhaus code')") parser.add_argument('-save_domains', action='store_true', help="Save full a domain sequences to file ('Stachelhaus code')") + parser.add_argument('-bacterial', action='store_true', + help="If given, run bacterial-only model") parser.add_argument('-s1', type=str, default=SEPARATOR_1, help="Symbol used as separator") parser.add_argument('-s2', type=str, default=SEPARATOR_2, help="Symbol used as separator") @@ -84,10 +86,14 @@ def main() -> None: if not substrate_names and args.exclude_standard_substrates: raise ValueError("No substrates to test! Either include standard substrates or pass custom substrate SMILES") - - model_path = download_and_unpack_or_fetch( - r"https://zenodo.org/records/17155186/files/model.parasect.gz?download=1", - temp_dir, logger) + if not args.bacterial: + model_path = download_and_unpack_or_fetch( + r"https://zenodo.org/records/17224548/files/model.parasect.gz?download=1", + temp_dir, logger) + else: + model_path = download_and_unpack_or_fetch( + r"https://zenodo.org/records/17224548/files/bacterial_model.parasect.gz?download=1", + temp_dir, logger) model = load(model_path) @@ -98,7 +104,8 @@ def main() -> None: custom_substrate_names=substrate_names, custom_substrate_smiles=substrate_smiles, only_custom=args.exclude_standard_substrates, - use_structure_guided_alignment=args.profile_alignment) + use_structure_guided_alignment=args.profile_alignment, + bacterial_only=args.bacterial) id_to_sig = {} id_to_ext = {} diff --git a/src/parasect/core/chem.py b/src/parasect/core/chem.py index 9c2ca43..010fe6c 100644 --- a/src/parasect/core/chem.py +++ b/src/parasect/core/chem.py @@ -73,6 +73,22 @@ def is_same_molecule_fingerprint(fingerprint_1: set[int], fingerprint_2: set[int return False +def get_jaccard_distance_from_fingerprint(fingerprint_1: set[int], fingerprint_2: set[int]) -> float: + """Return the jaccard distance between fingerprint_1 and fingerprint_2 + + :param fingerprint_1: ECFP fingerprint of molecule 1 + :type fingerprint_1: set[int] + :param fingerprint_2: ECFP fingerprint of molecule 2 + :type fingerprint_2: set[int] + :return: jaccard distance + :rtype: float + """ + + jaccard_index = len(fingerprint_1.intersection(fingerprint_2)) / len(fingerprint_1.union(fingerprint_2)) + jaccard_distance = 1 - jaccard_index + return jaccard_distance + + def smiles_to_fingerprint(smiles: str) -> set[int]: """Convert SMILES string to ECFP fingerprint. @@ -103,6 +119,7 @@ def get_fingerprint_hashes(substrates: set[Substrate], fingerprint_size: int) -> :rtype: list[int] """ hashes = [] + substrates = sorted(substrates, key=lambda x: x.name) for substrate in substrates: for chem_hash in substrate.fingerprint: @@ -110,12 +127,9 @@ def get_fingerprint_hashes(substrates: set[Substrate], fingerprint_size: int) -> counts = Counter(hashes) - hashes = [] - - for fingerprint_hash, count in counts.most_common(fingerprint_size): - hashes.append(fingerprint_hash) + sorted_hashes = sorted(counts.items(), key=lambda x: (-x[1], x[0])) - return hashes + return [fingerprint_hash for fingerprint_hash, _ in sorted_hashes[:fingerprint_size]] def fingerprint_to_bitvector(hashes: list[int], fingerprint: set[int]) -> list[int]: diff --git a/src/parasect/core/constants.py b/src/parasect/core/constants.py index 6af267d..6ada430 100644 --- a/src/parasect/core/constants.py +++ b/src/parasect/core/constants.py @@ -86,7 +86,9 @@ def get_path(file_name: str) -> str: SMILES_FILE = get_path("database_files/smiles.tsv") FINGERPRINTS_FILE = get_path("fingerprints.txt") +BACTERIAL_FINGERPRINTS_FILE = get_path("fingerprints_bacterial.txt") INCLUDED_SUBSTRATES_FILE = get_path("included_substrates.txt") +INCLUDED_SUBSTRATES_FILE_BACTERIAL = get_path("included_substrates_bacterial.txt") HMM2_POSITIONS_SIGNATURE = _read_positions(A_POSITION_FILE_HMM2, 0) HMM2_POSITIONS_EXTENDED_SIGNATURE = _read_positions(A_POSITION_FILE_34_HMM2, 0) diff --git a/src/parasect/core/parsing.py b/src/parasect/core/parsing.py index 7909f8f..97e3e15 100644 --- a/src/parasect/core/parsing.py +++ b/src/parasect/core/parsing.py @@ -12,7 +12,7 @@ from numpy.typing import NDArray from parasect.core.chem import smiles_to_fingerprint -from parasect.core.constants import FINGERPRINTS_FILE +from parasect.core.constants import FINGERPRINTS_FILE, BACTERIAL_FINGERPRINTS_FILE from parasect.core.tabular import Tabular @@ -290,13 +290,14 @@ def parse_fasta_file(path_in: str) -> Dict[str, str]: def data_from_substrate_names( - substrate_names: List[str], -) -> Tuple[List[str], List[str], List[List[int]]]: + substrate_names: List[str], bacterial_only: bool = False) -> Tuple[List[str], List[str], List[List[int]]]: """Return substrate names and fingerprints for all substrate names for which a fingerprint could be found. :param substrate_names: Substrate names. If the substrate name is not in the fingerprint file, a warning will be logged. :type substrate_names: List[str] + :param bacterial_only: Only use fingerprints from bacterial model + :type bacterial_only: bool :return: Substrate names, SMILES strings, and fingerprints. :rtype: Tuple[List[str], List[str], List[List[int]]] @@ -305,7 +306,12 @@ def data_from_substrate_names( """ logger = logging.getLogger(__name__) - data = Tabular(path_in=FINGERPRINTS_FILE, separator="\t") + if bacterial_only: + fingerprints_file = BACTERIAL_FINGERPRINTS_FILE + else: + fingerprints_file = FINGERPRINTS_FILE + + data = Tabular(path_in=fingerprints_file, separator="\t") ordered_substrate_names = [] ordered_substrate_smiles = [] diff --git a/src/parasect/data/fingerprints_bacterial.txt b/src/parasect/data/fingerprints_bacterial.txt new file mode 100644 index 0000000..25ca94f --- /dev/null +++ b/src/parasect/data/fingerprints_bacterial.txt @@ -0,0 +1,31 @@ +substrate_name smiles 829081502 1258652603 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0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 diff --git a/src/parasect/data/included_substrates_bacterial.txt b/src/parasect/data/included_substrates_bacterial.txt new file mode 100644 index 0000000..2a40390 --- /dev/null +++ b/src/parasect/data/included_substrates_bacterial.txt @@ -0,0 +1,30 @@ +2,3-diaminopropionic acid +2,3-dihydroxybenzoic acid +2,4-diaminobutyric acid +3,5-dihydroxyphenylglycine +4-hydroxyphenylglycine +N5-formyl-N5-hydroxyornithine +N5-hydroxyornithine +R-beta-hydroxytyrosine +alanine +arginine +asparagine +aspartic acid +beta-alanine +cysteine +glutamic acid +glutamine +glycine +histidine +isoleucine +leucine +lysine +ornithine +phenylalanine +pipecolic acid +proline +serine +threonine +tryptophan +tyrosine +valine diff --git a/src/parasect/database/flatfiles_from_db.py b/src/parasect/database/flatfiles_from_db.py index ea1647d..08fbaeb 100644 --- a/src/parasect/database/flatfiles_from_db.py +++ b/src/parasect/database/flatfiles_from_db.py @@ -1,11 +1,16 @@ import os from argparse import ArgumentParser, Namespace +from collections import Counter from sqlalchemy import create_engine, select from sqlalchemy.orm import Session + +from parasect.core.chem import get_jaccard_distance_from_fingerprint from parasect.database.build_database import AdenylationDomain, Protein, Substrate +from parasect.database.query_database import get_domains_from_synonym from parasect.core.writers import write_list +from parasect.core.parsing import parse_list def parse_arguments() -> Namespace: @@ -21,9 +26,81 @@ def parse_arguments() -> Namespace: return args +def substrates_to_cytoscape(session: Session, out_dir: str) -> None: + """Write substrate tables for cytoscape analysis from database + + :param session: database session + :type session: Session + :param out_dir: output directory + :type out_dir: str + """ + if not os.path.exists(out_dir): + os.mkdir(out_dir) + + counts_out = os.path.join(out_dir, "counts.txt") + distances_out = os.path.join(out_dir, "distances.txt") + all_substrates = list(session.scalars(select(Substrate)).all()) + + with open(counts_out, 'w') as out: + + for substrate in all_substrates: + count = len(substrate.domains) + + if count > 100: + out.write(f"{substrate.name}\t4\n") + elif count > 50: + out.write(f"{substrate.name}\t3\n") + elif count > 10: + out.write(f"{substrate.name}\t2\n") + elif count > 0: + out.write(f"{substrate.name}\t1\n") + with open(distances_out, 'w') as out: + out.write("substrate_1\tsubstrate_2\tdistance\n") + for i, substrate_1 in enumerate(all_substrates): + for j, substrate_2 in enumerate(all_substrates): + if j > i and len(substrate_1.domains) > 0 and len(substrate_2.domains) > 0: + distance = get_jaccard_distance_from_fingerprint(set(substrate_1.fingerprint), set(substrate_2.fingerprint)) + out.write(f"{substrate_1.name}\t{substrate_2.name}\t{distance}\n") + + +def taxonomy_to_alluvial(session: Session, out_file: str) -> None: + """ + Write taxonomy distribution to file which counts occurrences of domain-kingdom-phylum combinations + + :param session: database session + :type session: Session + :param out_file: path to output file + :type out_file: str + """ + tax_list = [] + for domain in list(session.scalars(select(AdenylationDomain)).all()): + taxonomy = domain.proteins[0].protein.taxonomy + domain = taxonomy.domain if taxonomy.domain is not None else "Unknown" + kingdom = taxonomy.kingdom if taxonomy.kingdom is not None else "Unknown" + phylum = taxonomy.phylum if taxonomy.phylum is not None else "Unknown" + tax_list.append((domain, kingdom, phylum)) + + counter = Counter(tax_list) + with open(out_file, 'w') as out: + out.write(f"Number\tDomain\tKingdom\tPhylum\n") + for tax, count in counter.items(): + out.write(f"{count}\t{tax[0]}\t{tax[1]}\t{tax[2]}\n") + + def write_substrate_names(session: Session, out_path: str) -> None: + """Write substrates from database to file + + :param session: database session + :type session: Session + :param out_path: path to output directory + :type out_path: str + """ all_substrates = list(session.scalars(select(Substrate)).all()) - write_list([s.name for s in all_substrates], out_path) + substrate_names = [] + for substrate in all_substrates: + if len(substrate.domains) > 0: + substrate_names.append(substrate.name) + write_list(substrate_names, out_path) def write_domain_names(session: Session, out_path: str) -> None: @@ -31,6 +108,17 @@ def write_domain_names(session: Session, out_path: str) -> None: write_list([d.get_name() for d in all_domains], out_path) +def write_domains_fasta(session: Session, domain_path: str, out_path: str) -> None: + domain_names = parse_list(domain_path) + domains = [] + for name in domain_names: + domains.append(get_domains_from_synonym(session, name.split('|')[0])[0]) + + with open(out_path, 'w') as out: + for domain in domains: + out.write(f">{domain.get_name()}\n{domain.sequence}\n") + + def db_to_flatfiles(database_path: str, out_dir: str) -> None: """Write database entries to machine-readable flatfiles (.fasta, .tsv, .txt) @@ -78,9 +166,11 @@ def db_to_flatfiles(database_path: str, out_dir: str) -> None: with open(substrates_path, 'w') as substrates_out: substrates_out.write("substrate\tsmiles\n") for substrate in substrates: - substrates_out.write(f"{substrate.name}\t{substrate.smiles}\n") + if len(substrate.domains) > 0: + substrates_out.write(f"{substrate.name}\t{substrate.smiles}\n") if __name__ == "__main__": args = parse_arguments() db_to_flatfiles(args.db, args.o) + From d5caf9ac653c1740c01c3e677e7d141303a41baf Mon Sep 17 00:00:00 2001 From: David Meijer Date: Tue, 30 Sep 2025 20:29:45 +0200 Subject: [PATCH 60/65] WIP: adding parasect bacterial mode to frontend --- app/src/client/src/components/SettingsModal.js | 6 ++++-- app/src/client/src/pages/submit.js | 14 ++++++++++++-- app/src/server/routes/submit.py | 13 +++++++++---- 3 files changed, 25 insertions(+), 8 deletions(-) diff --git a/app/src/client/src/components/SettingsModal.js b/app/src/client/src/components/SettingsModal.js index 342f2a8..18d68fd 100644 --- a/app/src/client/src/components/SettingsModal.js +++ b/app/src/client/src/components/SettingsModal.js @@ -133,7 +133,9 @@ const SettingsModal = ({ variant='body1' gutterBottom style={{ - color: selectedModel !== 'parasect' ? 'rgba(0, 0, 0, 0.26)' : 'rgba(0, 0, 0, 0.87)' + color: (selectedModel !== 'parasect' || selectedModel !== 'parasectBacterial') + ? 'rgba(0, 0, 0, 0.26)' + : 'rgba(0, 0, 0, 0.87)' }} > Upload custom list of substrates (TSV format as 'name\tSMILES' per line): @@ -142,7 +144,7 @@ const SettingsModal = ({ type='file' inputProps={{ accept: '.tsv' }} onChange={handleSmilesFileUpload} - disabled={selectedModel !== 'parasect'} + disabled={!(selectedModel === 'parasect' || selectedModel === 'parasectBacterial')} /> diff --git a/app/src/client/src/pages/submit.js b/app/src/client/src/pages/submit.js index 58ce2ad..80864d8 100644 --- a/app/src/client/src/pages/submit.js +++ b/app/src/client/src/pages/submit.js @@ -1,7 +1,7 @@ import React, { useState } from 'react'; import { toast } from 'react-toastify'; import { Box, Button, Divider, TextField, FormControl, FormLabel, RadioGroup, FormControlLabel, Radio, CircularProgress, Typography, Input } from '@mui/material'; -import { MdSettings } from 'react-icons/md'; +import { MdSettings, MdBugReport } from 'react-icons/md'; import SettingsModal from '../components/SettingsModal'; @@ -240,9 +240,19 @@ const Submit = () => { label={ } /> + } + label={ + + } + /> diff --git a/app/src/server/routes/submit.py b/app/src/server/routes/submit.py index ef04902..1eb3d1a 100644 --- a/app/src/server/routes/submit.py +++ b/app/src/server/routes/submit.py @@ -25,12 +25,14 @@ MODEL_PARAS_ALL_SUBSTRATES = os.path.join(MODEL_DIR, "all_substrates_model.paras") MODEL_PARAS_COMMON_SUBSTRATES = os.path.join(MODEL_DIR, "model.paras") MODEL_PARASECT = os.path.join(MODEL_DIR, "model.parasect") +MODEL_PARASECT_BACTERIAL = os.path.join(MODEL_DIR, "bacterial_model.parasect") loader = MultiModelLoader({ "parasAllSubstrates": ModelSpec(name="PARAS (all substrates)", path=MODEL_PARAS_ALL_SUBSTRATES, mmap=True), "parasCommonSubstrates": ModelSpec(name="PARAS (common substrates)", path=MODEL_PARAS_COMMON_SUBSTRATES, mmap=True), - "parasect": ModelSpec(name="PARASECT", path=MODEL_PARASECT, mmap=True) + "parasect": ModelSpec(name="PARASECT", path=MODEL_PARASECT, mmap=True), + "parasectBacterial": ModelSpec(name="PARASECT (bacterial)", path=MODEL_PARASECT_BACTERIAL, mmap=True), }) @@ -64,7 +66,7 @@ def run_prediction_raw(job_id: str, data: Dict[str, str]) -> None: selected_input = data["selectedInput"] # fasta src or gbk src selected_model = data[ "selectedModel" - ] # parasAllSubstrates, parasCommonSubstrates, or parasect + ] # parasAllSubstrates, parasCommonSubstrates, parasect, or parasectBacterial use_structure_guided_alignment = data["useStructureGuidedAlignment"] smiles_file_content = data["smilesFileContent"] use_only_uploaded_substrates = data["useOnlyUploadedSubstrates"] @@ -83,7 +85,7 @@ def run_prediction_raw(job_id: str, data: Dict[str, str]) -> None: # sanity check selected model # return with message if invalid selected_model = selected_model.strip() - if selected_model not in ["parasAllSubstrates", "parasCommonSubstrates", "parasect"]: + if selected_model not in ["parasAllSubstrates", "parasCommonSubstrates", "parasect", "parasectBacterial"]: msg = f"invalid model: {selected_model}" raise Exception(msg) @@ -116,7 +118,7 @@ def run_prediction_raw(job_id: str, data: Dict[str, str]) -> None: use_structure_guided_alignment=use_structure_guided_alignment, ) - elif selected_model == "parasect": + elif selected_model in ["parasect", "parasectBacterial"]: # parse user-provided SMILES strings (if provided in frontend) # return error if failed custom_substrate_names = [] @@ -150,6 +152,9 @@ def run_prediction_raw(job_id: str, data: Dict[str, str]) -> None: # return with error message that at least one custom substrate must be provided in that case if len(custom_substrate_names) == 0 and use_only_uploaded_substrates: raise Exception("at least one custom substrate must be provided if 'Use only uploaded substrates' is selected.") + + # Print excpected feature vector length for debugging + print(f"Using model {selected_model} with expected feature vector length {model.n_features_in_}") # run PARASECT results = run_parasect( From eda9d32b4962ffb4c036b0e8af3a2e904643db00 Mon Sep 17 00:00:00 2001 From: David Meijer Date: Tue, 30 Sep 2025 20:46:15 +0200 Subject: [PATCH 61/65] ENH: parasect bacterial mode functional --- app/src/server/routes/submit.py | 1 + 1 file changed, 1 insertion(+) diff --git a/app/src/server/routes/submit.py b/app/src/server/routes/submit.py index 1eb3d1a..2795cf9 100644 --- a/app/src/server/routes/submit.py +++ b/app/src/server/routes/submit.py @@ -166,6 +166,7 @@ def run_prediction_raw(job_id: str, data: Dict[str, str]) -> None: custom_substrate_smiles=custom_substrate_smiles, only_custom=use_only_uploaded_substrates, use_structure_guided_alignment=use_structure_guided_alignment, + bacterial_only=(selected_model == "parasectBacterial"), ) else: From 78b5380789d6a79028c11946e50c6a0c424fb848 Mon Sep 17 00:00:00 2001 From: David Meijer Date: Tue, 30 Sep 2025 20:47:05 +0200 Subject: [PATCH 62/65] STY: fixed typos --- app/src/client/src/pages/submit.js | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/app/src/client/src/pages/submit.js b/app/src/client/src/pages/submit.js index 80864d8..547f334 100644 --- a/app/src/client/src/pages/submit.js +++ b/app/src/client/src/pages/submit.js @@ -240,7 +240,7 @@ const Submit = () => { label={ } /> { label={ } /> From 75aa24065585f79ca680b8c9b24b383c9a3dca69 Mon Sep 17 00:00:00 2001 From: David Meijer Date: Mon, 6 Oct 2025 13:45:12 +0200 Subject: [PATCH 63/65] WIP: add navigation query database page --- app/src/client/src/index.js | 10 ++++++++++ app/src/client/src/pages/home.js | 11 +++++++++++ app/src/client/src/pages/query_database.js | 11 +++++++++++ 3 files changed, 32 insertions(+) create mode 100644 app/src/client/src/pages/query_database.js diff --git a/app/src/client/src/index.js b/app/src/client/src/index.js index c4baf44..7b47a79 100644 --- a/app/src/client/src/index.js +++ b/app/src/client/src/index.js @@ -9,6 +9,7 @@ import UploadIcon from '@mui/icons-material/Upload'; import GitHubIcon from '@mui/icons-material/GitHub'; import RetrieveIcon from '@mui/icons-material/GetApp'; import DatasetIcon from '@mui/icons-material/Dataset' +import QueryStatsIcon from '@mui/icons-material/QueryStats'; import './style/main.css'; @@ -20,6 +21,7 @@ import Results from './pages/results'; import NotFound from './pages/not_found'; import DataAnnotation from './pages/data_annotation' import AnnotationEditor from './pages/annotation_editor' +import QueryDatabase from './pages/query_database' /** * Custom theme for the app. @@ -139,6 +141,10 @@ const CustomToolbar = () => { Data annotation + handleMenuItemClick('/query_database')}> + + Query database + handleExternalLinkClick('https://github.com/BTheDragonMaster/parasect/issues')}> Report an issue @@ -192,6 +198,10 @@ function AppRoutes () { path='/data_annotation' element={} /> + } + /> } diff --git a/app/src/client/src/pages/home.js b/app/src/client/src/pages/home.js index 0cbd82b..c3eebdc 100644 --- a/app/src/client/src/pages/home.js +++ b/app/src/client/src/pages/home.js @@ -83,6 +83,17 @@ const Home = () => { Annotate domain + diff --git a/app/src/client/src/pages/query_database.js b/app/src/client/src/pages/query_database.js new file mode 100644 index 0000000..547b7a1 --- /dev/null +++ b/app/src/client/src/pages/query_database.js @@ -0,0 +1,11 @@ +import Reacs from 'react'; +import { toast } from 'react-toastify'; + + +const QueryDatabase = () => { + return ( +

Query Database Page
+ ); +}; + +export default QueryDatabase; \ No newline at end of file From a59f8c78003a691f448b051fd8fd89d08a0bb110 Mon Sep 17 00:00:00 2001 From: David Meijer Date: Mon, 6 Oct 2025 20:02:28 +0200 Subject: [PATCH 64/65] ENH: database querying --- app/src/client/package-lock.json | 23591 +++++------------- app/src/client/package.json | 11 +- app/src/client/src/components/Statistics.js | 104 + app/src/client/src/pages/query_database.js | 494 +- app/src/server/api.py | 14 +- app/src/server/routes/constants.py | 6 + app/src/server/routes/sql.py | 181 + 7 files changed, 7265 insertions(+), 17136 deletions(-) create mode 100644 app/src/client/src/components/Statistics.js create mode 100644 app/src/server/routes/sql.py diff --git a/app/src/client/package-lock.json b/app/src/client/package-lock.json index 966a5f5..e9615d8 100644 --- a/app/src/client/package-lock.json +++ b/app/src/client/package-lock.json @@ -1,17 +1,19 @@ { "name": "paras-webapp", "version": "2.0.0", - "lockfileVersion": 2, + "lockfileVersion": 3, "requires": true, "packages": { "": { "name": "paras-webapp", "version": "2.0.0", "dependencies": { - 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Please use @babel/plugin-transform-nullish-coalescing-operator instead.", + "license": "MIT", "dependencies": { "@babel/helper-plugin-utils": "^7.18.6", "@babel/plugin-syntax-nullish-coalescing-operator": "^7.8.3" @@ -713,6 +599,7 @@ "resolved": "https://registry.npmjs.org/@babel/plugin-proposal-numeric-separator/-/plugin-proposal-numeric-separator-7.18.6.tgz", "integrity": "sha512-ozlZFogPqoLm8WBr5Z8UckIoE4YQ5KESVcNudyXOR8uqIkliTEgJ3RoketfG6pmzLdeZF0H/wjE9/cCEitBl7Q==", "deprecated": "This proposal has been merged to the ECMAScript standard and thus this plugin is no longer maintained. Please use @babel/plugin-transform-numeric-separator instead.", + "license": "MIT", "dependencies": { "@babel/helper-plugin-utils": "^7.18.6", "@babel/plugin-syntax-numeric-separator": "^7.10.4" @@ -729,6 +616,7 @@ "resolved": "https://registry.npmjs.org/@babel/plugin-proposal-optional-chaining/-/plugin-proposal-optional-chaining-7.21.0.tgz", "integrity": "sha512-p4zeefM72gpmEe2fkUr/OnOXpWEf8nAgk7ZYVqqfFiyIG7oFfVZcCrU64hWn5xp4tQ9LkV4bTIa5rD0KANpKNA==", "deprecated": "This proposal has been merged to the ECMAScript standard and thus this plugin is no longer maintained. Please use @babel/plugin-transform-optional-chaining instead.", + "license": "MIT", "dependencies": { "@babel/helper-plugin-utils": "^7.20.2", "@babel/helper-skip-transparent-expression-wrappers": "^7.20.0", @@ -746,6 +634,7 @@ "resolved": "https://registry.npmjs.org/@babel/plugin-proposal-private-methods/-/plugin-proposal-private-methods-7.18.6.tgz", "integrity": "sha512-nutsvktDItsNn4rpGItSNV2sz1XwS+nfU0Rg8aCx3W3NOKVzdMjJRu0O5OkgDp3ZGICSTbgRpxZoWsxoKRvbeA==", "deprecated": "This proposal has been merged to the ECMAScript standard and thus this plugin is no longer maintained. Please use @babel/plugin-transform-private-methods instead.", + "license": "MIT", "dependencies": { "@babel/helper-create-class-features-plugin": "^7.18.6", "@babel/helper-plugin-utils": "^7.18.6" @@ -761,6 +650,7 @@ "version": "7.21.0-placeholder-for-preset-env.2", "resolved": "https://registry.npmjs.org/@babel/plugin-proposal-private-property-in-object/-/plugin-proposal-private-property-in-object-7.21.0-placeholder-for-preset-env.2.tgz", "integrity": "sha512-SOSkfJDddaM7mak6cPEpswyTRnuRltl429hMraQEglW+OkovnCzsiszTmsrlY//qLFjCpQDFRvjdm2wA5pPm9w==", + "license": "MIT", "engines": { "node": ">=6.9.0" }, @@ -772,6 +662,7 @@ "version": "7.8.4", "resolved": "https://registry.npmjs.org/@babel/plugin-syntax-async-generators/-/plugin-syntax-async-generators-7.8.4.tgz", "integrity": "sha512-tycmZxkGfZaxhMRbXlPXuVFpdWlXpir2W4AMhSJgRKzk/eDlIXOhb2LHWoLpDF7TEHylV5zNhykX6KAgHJmTNw==", + "license": "MIT", "dependencies": { "@babel/helper-plugin-utils": "^7.8.0" }, @@ -783,6 +674,7 @@ "version": 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They can almost certainly migrate to the native JavaScript promise now. Thank you literally everyone for joining me in this bet against the odds. Be excellent to each other.\n\n(For a CapTP with native promises, see @endo/eventual-send and @endo/captp)", + "license": "MIT", "engines": { "node": ">=0.6.0", "teleport": ">=0.2.0" } }, "node_modules/qs": { - "version": "6.11.0", - "resolved": "https://registry.npmjs.org/qs/-/qs-6.11.0.tgz", - "integrity": "sha512-MvjoMCJwEarSbUYk5O+nmoSzSutSsTwF85zcHPQ9OrlFoZOYIjaqBAJIqIXjptyD5vThxGq52Xu/MaJzRkIk4Q==", + "version": "6.13.0", + "resolved": "https://registry.npmjs.org/qs/-/qs-6.13.0.tgz", + "integrity": "sha512-+38qI9SOr8tfZ4QmJNplMUxqjbe7LKvvZgWdExBOmd+egZTtjLB67Gu0HRX3u/XOq7UU2Nx6nsjvS16Z9uwfpg==", + "license": "BSD-3-Clause", "dependencies": { - "side-channel": "^1.0.4" + "side-channel": "^1.0.6" }, "engines": { "node": ">=0.6" @@ -15064,7 +17208,8 @@ "node_modules/querystringify": { "version": "2.2.0", "resolved": "https://registry.npmjs.org/querystringify/-/querystringify-2.2.0.tgz", - "integrity": "sha512-FIqgj2EUvTa7R50u0rGsyTftzjYmv/a3hO345bZNrqabNqjtgiDMgmo4mkUjd+nzU5oF3dClKqFIPUKybUyqoQ==" + "integrity": "sha512-FIqgj2EUvTa7R50u0rGsyTftzjYmv/a3hO345bZNrqabNqjtgiDMgmo4mkUjd+nzU5oF3dClKqFIPUKybUyqoQ==", + "license": "MIT" }, "node_modules/queue-microtask": { "version": "1.2.3", @@ -15083,12 +17228,14 @@ "type": "consulting", "url": "https://feross.org/support" } - 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"@emotion/react": "^11.13.3", - "@emotion/styled": "^11.13.0", - "@mui/icons-material": "^6.1.3", - "@mui/material": "^6.1.3", + "@emotion/react": "^11.14.0", + "@emotion/styled": "^11.14.1", + "@mui/icons-material": "^6.5.0", + "@mui/material": "^6.5.0", + "@mui/system": "^6.5.0", + "@mui/x-data-grid": "^7.29.9", "@testing-library/jest-dom": "^5.16.4", "@testing-library/react": "^13.3.0", "@testing-library/user-event": "^13.5.0", @@ -17,6 +19,7 @@ "react-scripts": "5.0.1", "react-toastify": "^9.1.3", "react-turnstile": "^1.1.4", + "recharts": "^3.2.1", "smiles-drawer": "^2.1.7" }, "scripts": { diff --git a/app/src/client/src/components/Statistics.js b/app/src/client/src/components/Statistics.js new file mode 100644 index 0000000..ce2a601 --- /dev/null +++ b/app/src/client/src/components/Statistics.js @@ -0,0 +1,104 @@ +import React, { useEffect, useMemo, useState } from 'react'; +import { Box, Card, CardContent, CardHeader, LinearProgress, Typography } from '@mui/material'; +import { ResponsiveContainer, PieChart, Pie, Tooltip, Legend, Cell } from 'recharts'; +import { toast } from 'react-toastify'; + +const SQL_ANNOTATED_BY_DOMAIN = ` +SELECT + t.domain AS label, + COUNT(DISTINCT ad.id) AS value +FROM adenylation_domain ad +JOIN substrate_domain_association sda ON sda.domain_id = ad.id -- annotated only +JOIN protein_domain_association pda ON pda.domain_id = ad.id +JOIN protein p ON p.id = pda.protein_id +JOIN taxonomy t ON t.id = p.taxonomy_id +GROUP BY t.domain +ORDER BY value DESC +`; + +const COLORS = [ + '#8884d8', '#82ca9d', '#ffc658', '#8dd1e1', '#a4de6c', + '#d0ed57', '#ffa07a', '#90ee90', '#87cefa', '#ffb6c1' +]; + +export default function Statistics() { + const [rows, setRows] = useState([]); + const [loading, setLoading] = useState(false); + + // Fetch once on mount + useEffect(() => { + let cancelled = false; + (async () => { + setLoading(true); + try { + const res = await fetch('/api/sql', { + method: 'POST', + headers: { 'Content-Type': 'application/json' }, + body: JSON.stringify({ + query: SQL_ANNOTATED_BY_DOMAIN, + page: 0, + pageSize: 1000, + sortBy: null, + sortDir: null, + }), + }); + if (!res.ok) throw new Error(await res.text()); + const data = await res.json(); + if (!cancelled) setRows(Array.isArray(data.rows) ? data.rows : []); + } catch (e) { + if (!cancelled) toast.error(`Failed to load stats: ${e.message}`); + } finally { + if (!cancelled) setLoading(false); + } + })(); + return () => { cancelled = true; }; + }, []); + + const chartData = useMemo(() => { + // Expecting rows like: [{ label: 'Bacteria', value: 123 }, ...] + return rows.map((r) => ({ + label: `${r.label} (${r.value})` ?? 'Unknown', + value: Number(r.value ?? 0), + })).filter(d => d.value > 0); + }, [rows]); + + return ( + + + + {loading && ( + + + + )} + {chartData.length === 0 && !loading ? ( + + No data + + ) : ( + + + + {chartData.map((entry, idx) => ( + + ))} + + + + + + )} + + + ); +} + diff --git a/app/src/client/src/pages/query_database.js b/app/src/client/src/pages/query_database.js index 547b7a1..49bd593 100644 --- a/app/src/client/src/pages/query_database.js +++ b/app/src/client/src/pages/query_database.js @@ -1,11 +1,495 @@ -import Reacs from 'react'; +import { useCallback, useEffect, useMemo, useRef, useState } from 'react'; import { toast } from 'react-toastify'; +import { + Box, + Button, + Divider, + LinearProgress, + Stack, + TextField, + Typography, + Select, + MenuItem, + InputLabel, +} from '@mui/material'; +import SearchIcon from '@mui/icons-material/Search'; +import ClearIcon from '@mui/icons-material/Clear'; +import DownloadIcon from '@mui/icons-material/Download'; +import { DataGrid, GridToolbarContainer, GridPagination } from '@mui/x-data-grid'; +import Statistics from '../components/Statistics'; +const DEFAULT_PAGE_SIZE = 100; +const MAX_EXPORT_ROWS = 100000; + +const QUERYOPTIONS = [ + // { + // key: 'free', + // label: 'Free-form SQL', + // kind: 'free', + // defaultQuery: 'SELECT name, smiles FROM substrate LIMIT 500', + // Editor: ({ query, setQuery }) => ( + // setQuery(e.target.value)} + // fullWidth + // multiline + // minRows={3} + // placeholder="e.g., SELECT * FROM substrate LIMIT 500" + // /> + // ), + // }, + { + key: 'proteinId', + label: 'Substrate specificities by protein ID', + kind: 'preset', + defaultQuery: "SELECT * FROM protein_synonym LIMIT 500", + // Editor compiles SQL directly into the main query state + Editor: ({ presetInput, setPresetInput, setQuery }) => ( + { + const v = e.target.value; + setPresetInput(v); + const t = v.trim(); + setQuery( + t + ? ` + SELECT + ad.id AS domain_id, + p.id AS protein_id, + ps.synonym AS protein_synonym, + pda.domain_number, + ad.signature, + ad.extended_signature, + s.name AS substrate_name, + s.smiles AS substrate_smiles + FROM protein_synonym ps + JOIN protein p ON p.id = ps.protein_id + JOIN protein_domain_association pda ON pda.protein_id = p.id + JOIN adenylation_domain ad ON ad.id = pda.domain_id + LEFT JOIN substrate_domain_association sda ON sda.domain_id = ad.id + LEFT JOIN substrate s ON s.name = sda.substrate_name + WHERE ps.synonym = '${t}' COLLATE NOCASE + ORDER BY pda.domain_number, s.name + LIMIT 500 + `.replace(/\s+/g, ' ').trim() + : '' + ); + }} + fullWidth + placeholder="e.g., P48633.1" + /> + ), + }, + { + key: 'species', + label: 'Substrate specificities by species', + kind: 'preset', + defaultQuery: "SELECT DISTINCT species FROM taxonomy LIMIT 500", + // Editor compiles SQL directly into the main query state + Editor: ({ presetInput, setPresetInput, setQuery }) => ( + { + const v = e.target.value; + setPresetInput(v); + const t = v.trim(); + setQuery( + t + ? ` + SELECT + ad.id AS domain_id, + p.id AS protein_id, + t.species AS species, + pda.domain_number, + ad.signature, + ad.extended_signature, + s.name AS substrate_name, + s.smiles AS substrate_smiles + FROM taxonomy t + JOIN protein p ON p.taxonomy_id = t.id + JOIN protein_domain_association pda ON pda.protein_id = p.id + JOIN adenylation_domain ad ON ad.id = pda.domain_id + LEFT JOIN substrate_domain_association sda ON sda.domain_id = ad.id + LEFT JOIN substrate s ON s.name = sda.substrate_name + WHERE t.species = '${t}' COLLATE NOCASE + ORDER BY pda.domain_number, s.name + LIMIT 500 + `.replace(/\s+/g, ' ').trim() + : '' + ); + }} + fullWidth + placeholder="e.g., Streptomyces coelicolor" + /> + ), + }, + { + key: 'signature', + label: 'Substrate specificities by A-domain signature (Hamming ≤ N)', + kind: 'preset', + defaultQuery: "SELECT * FROM adenylation_domain LIMIT 500", + // Local state inside editor; compiles SQL into `query` (no parsing back) + Editor: ({ setQuery }) => { + const [sig, setSig] = useState(''); + const [maxDist, setMaxDist] = useState(3); // sensible default + + const updateSQL = (s, d) => { + const clamped = Math.max(0, Math.min(10, Number.isFinite(+d) ? +d : 0)); + const pad = s.toUpperCase().slice(0, 10).padEnd(10, '-'); // GAP token '-' + // build 10 char-by-char comparisons + const comps = Array.from({ length: 10 }, (_, i) => { + const idx = i + 1; + return `(substr('${pad}',${idx},1) <> substr(UPPER(substr(ad.signature || '----------',1,10)),${idx},1))`; + }).join(' + '); + const sql = ` + WITH d AS ( + SELECT + ad.id, + ad.signature, + ad.extended_signature, + (${comps}) AS hamming + FROM adenylation_domain ad + ) + SELECT + d.id AS domain_id, + p.id AS protein_id, + group_concat(ps.synonym, ', ') AS protein_synonyms + pda.domain_number, + ad.signature, + ad.extended_signature, + s.name AS substrate_name, + s.smiles AS substrate_smiles, + d.hamming, + FROM d + JOIN adenylation_domain ad ON ad.id = d.id + JOIN protein_domain_association pda ON pda.domain_id = ad.id + JOIN protein p ON p.id = pda.protein_id + LEFT JOIN substrate_domain_association sda ON sda.domain_id = ad.id + LEFT JOIN substrate s ON s.name = sda.substrate_name + LEFT JOIN protein_synonym ps ON ps.protein_id = p.id + WHERE d.hamming <= ${clamped} + GROUP BY + d.id, p.id, pda.domain_number, + ad.signature, ad.extended_signature, + s.name, s.smiles, d.hamming + ORDER BY pda.domain_number, s.name + LIMIT 500 + `.replace(/\s+/g, ' ').trim(); + setQuery(sql); + }; + + return ( + + { + const v = e.target.value; + setSig(v); + updateSQL(v, maxDist); + }} + fullWidth + placeholder="e.g., S/T-A-V-I-G-H-D-L" + /> + { + const v = e.target.value; + setMaxDist(v); + updateSQL(sig, v); + }} + sx={{ width: 200 }} + /> + + ); + }, + }, +]; + +const CustomTopToolbar = () => ( + + + +); const QueryDatabase = () => { - return ( -
Query Database Page
- ); + // which query mode is active + const [selectedKey, setSelectedKey] = useState(QUERYOPTIONS[0].key); + const selectedOption = useMemo( + () => QUERYOPTIONS.find((o) => o.key === selectedKey) || QUERYOPTIONS[0], + [selectedKey] + ); + + const [presetInput, setPresetInput] = useState(''); + const [query, setQuery] = useState(selectedOption.defaultQuery || ''); + + // grid state + const [rows, setRows] = useState([]); + const [columns, setColumns] = useState([]); + const [loading, setLoading] = useState(false); + const [rowCount, setRowCount] = useState(0); + const [page, setPage] = useState(0); + const [pageSize, setPageSize] = useState(DEFAULT_PAGE_SIZE); + const [sortModel, setSortModel] = useState([]); + const lastRequestRef = useRef(0); + + // Memoized active sort parameters + const activeSort = useMemo(() => { + if (!sortModel.length) return { sortBy: null, sortDir: null }; + const { field, sort } = sortModel[0]; + return { sortBy: field, sortDir: sort }; + }, [sortModel]); + + // Function to build columns from sample rows + const buildColumnsFromRows = (sampleRows) => { + if (!sampleRows.length) return []; + const keys = Object.keys(sampleRows[0]); + return keys.map((k) => ({ + field: k, + headerName: k, + flex: 1, + minWidth: 120, + })) + }; + + // Ensure each row has a unique 'id' field for DataGrid + const ensureRowIds = (arr) => arr.map((r, i) => (r.id ? r : { id: `${page}-${i}`, ...r })); + + // Fetch results from the server + const fetchResults = useCallback(async ({ q, p, ps, sortBy, sortDir }) => { + if (!q.trim()) { + toast.warn('Please enter a SQL query.'); + return; + } + setLoading(true); + const reqId = Date.now(); + lastRequestRef.current = reqId; + try { + const res = await fetch('/api/sql', { + method: 'POST', + headers: { 'Content-Type': 'application/json' }, + body: JSON.stringify({ query: q, page: p, pageSize: ps, sortBy, sortDir }), + }) + if (!res.ok) throw new Error(await res.text()); + const data = await res.json(); + if (lastRequestRef.current !== reqId) return; + const cols = data.columns?.length ? data.columns.map((c) => ({ flex: 1, minWidth: 120, ...c })) : buildColumnsFromRows(data.rows || []); + const withIds = ensureRowIds(data.rows || []); + setColumns(cols); + setRows(withIds); + setRowCount(Number.isFinite(data.total) ? data.total : withIds.length); + } catch (err) { + toast.error(`Query failed: ${err.message}`); + setColumns([]); + setRows([]); + setRowCount(0); + } finally { + setLoading(false); + } + }, [page, selectedOption]); + + // Fetch results when page, pageSize, or activeSort changes + const onSearch = useCallback(() => { + setPage(0); + fetchResults({ q: query, p: 0, ps: pageSize, ...activeSort }); + }, [query, pageSize, activeSort, fetchResults]); + + // Clear all results and reset state + const clearAll = () => { + setRows([]); + setColumns([]); + setRowCount(0); + setPage(0); + setSortModel([]); + // keep current query text; if preset is active and its editor cleared, query may be '' + }; + + // Export helpers + const makeDelimited = (cols, data, delim) => { + const header = cols.map((c) => c.field).join(delim); + const lines = data.map((r) => cols.map((c) => String(r[c.field] ?? '').replace(/\n|\r/g, ' ')).join(delim)); + return [header, ...lines].join('\n'); + }; + + const downloadFile = (content, filename, mime) => { + const blob = new Blob([content], { type: mime }); + const url = URL.createObjectURL(blob); + const a = document.createElement('a'); + a.href = url; + a.download = filename; + document.body.appendChild(a); + a.click(); + a.remove(); + URL.revokeObjectURL(url); + }; + + const exportCurrentPage = (format) => { + if (!columns.length || !rows.length) { + toast.info('Nothing to export.'); + return; + } + const delim = format === 'csv' ? ',' : '\t'; + const text = makeDelimited(columns, rows, delim); + downloadFile(text, `results_page${page + 1}.${format}`, format === 'csv' ? 'text/csv' : 'text/tab-separated-values'); + }; + + const exportAll = async (format) => { + setLoading(true); + try { + if (!query.trim()) return toast.warn('Please enter a SQL query first!'); + const res = await fetch('/api/sql', { + method: 'POST', + headers: { 'Content-Type': 'application/json' }, + body: JSON.stringify({ + query, + page: 0, + pageSize: MAX_EXPORT_ROWS, + sortBy: activeSort.sortBy, + sortDir: activeSort.sortDir, + }), + }); + if (!res.ok) throw new Error(await res.text()); + const data = await res.json(); + const cols = data.columns?.length ? data.columns.map((c) => ({ flex: 1, minWidth: 120, ...c })) : buildColumnsFromRows(data.rows || []); + const delim = format === 'csv' ? ',' : '\t'; + const text = makeDelimited(cols, data.rows || [], delim); + downloadFile(text, `results_all.${format}`, format === 'csv' ? 'text/csv' : 'text/tab-separated-values'); + } catch (err) { + toast.error(`Export failed: ${err.message}`); + } finally { + setLoading(false); + } + }; + + useEffect(() => { + // only refetch if we've already run at least once + if (!query.trim()) return; + if (rows.length === 0 && rowCount === 0) return; + fetchResults({ q: query, p: page, ps: pageSize, ...activeSort }); + }, [page, pageSize, activeSort.sortBy, activeSort.sortDir]); // eslint-disable-line react-hooks/exhaustive-deps + + return ( + + + Query database + + + + + + + + + Query mode + + + + {/* Per-option editor: + - 'free' shows SQL textarea + - presets render inputs that directly update the main query via setQuery + */} + {selectedOption.Editor ? ( + selectedOption.key === 'free' + ? + : + ) : null} + + + + + + + + + + {/* */} + + + + + + + + + { + if (model.pageSize !== pageSize) setPageSize(model.pageSize); + if (model.page !== page) setPage(model.page); + }} + sortingOrder={["asc", "desc"]} + sortModel={sortModel} + onSortModelChange={(model) => setSortModel(model)} + disableRowSelectionOnClick + loading={loading} + slots={{ + toolbar: CustomTopToolbar, + loadingOverlay: LinearProgress, + noRowsOverlay: () => ( + + + {rows.length === 0 && !loading ? 'Sorry, no results for query' : ''} + + + ), + }} + /> + + + {loading && ( + + + + )} + + ); }; -export default QueryDatabase; \ No newline at end of file +export default QueryDatabase; diff --git a/app/src/server/api.py b/app/src/server/api.py index 13ee6cc..8bbc92d 100644 --- a/app/src/server/api.py +++ b/app/src/server/api.py @@ -1,5 +1,4 @@ # -*- coding: utf-8 -*- - """API for PARSECT.""" from flask import Response, jsonify @@ -7,9 +6,15 @@ from routes.retrieval import blueprint_retrieve from routes.submit import blueprint_submit_raw, blueprint_submit_quick from routes.data_annotation import blueprint_annotate_data -from routes.annotation_editor import blueprint_check_smiles, blueprint_check_substrate_name, blueprint_get_substrates, \ - blueprint_submit_annotations, blueprint_check_protein_name, blueprint_check_domain_name -from routes.database import engine +from routes.annotation_editor import ( + blueprint_check_smiles, + blueprint_check_substrate_name, + blueprint_get_substrates, + blueprint_submit_annotations, + blueprint_check_protein_name, + blueprint_check_domain_name, +) +from routes.sql import blueprint_sql from parasect.version import get_version @@ -23,6 +28,7 @@ app.register_blueprint(blueprint_get_substrates) app.register_blueprint(blueprint_submit_annotations) app.register_blueprint(blueprint_check_protein_name) +app.register_blueprint(blueprint_sql) @app.errorhandler(404) diff --git a/app/src/server/routes/constants.py b/app/src/server/routes/constants.py index f2bd3d4..941f942 100644 --- a/app/src/server/routes/constants.py +++ b/app/src/server/routes/constants.py @@ -10,3 +10,9 @@ ) MODEL_DIR = os.getenv("MODEL_DIR", MODEL_DIR_LOCAL) TEMP_DIR = os.path.join(os.path.dirname(os.path.dirname(os.path.abspath(__file__))), "temp") + +DB_PATH_LOCAL = os.path.join( + os.path.dirname(os.path.dirname(os.path.abspath(__file__))), + "parasect.db", +) +DB_PATH = os.getenv("SQLITE_PATH", DB_PATH_LOCAL) \ No newline at end of file diff --git a/app/src/server/routes/sql.py b/app/src/server/routes/sql.py new file mode 100644 index 0000000..0503324 --- /dev/null +++ b/app/src/server/routes/sql.py @@ -0,0 +1,181 @@ +# routes/sql.py +# -*- coding: utf-8 -*- +""" +Read-only SQL query endpoints for SQLite. + +POST /api/sql -> paginated JSON for DataGrid +POST /api/sql/export -> streamed CSV/TSV download +""" + +from __future__ import annotations +import os +import re +import sqlite3 +import time +from typing import List, Optional + +from flask import Blueprint, request, jsonify, abort, Response + +try: + from routes.database import engine as sa_engine # Optional +except Exception: + sa_engine = None + +blueprint_sql = Blueprint("blueprint_sql", __name__) + +DB_PATH = os.getenv("SQLITE_PATH", None) # can be set via env +MAX_PAGE_SIZE = int(os.getenv("MAX_PAGE_SIZE", "1000")) +MAX_EXPORT_ROWS = int(os.getenv("MAX_EXPORT_ROWS", "100000")) +QUERY_TIMEOUT_SECS = float(os.getenv("QUERY_TIMEOUT_SECS", "30")) + +SELECT_LIKE = re.compile(r"^\s*(select|with)\b", re.IGNORECASE) +IDENT = re.compile(r"[A-Za-z_][A-Za-z0-9_]*$") + + +def _resolve_sqlite_path() -> str: + """Prefer SQLITE_PATH; else, try to derive from SQLAlchemy engine if it's SQLite; else fallback.""" + if DB_PATH: + return DB_PATH + try: + if sa_engine is not None and sa_engine.url and sa_engine.url.get_backend_name().startswith("sqlite"): + # this is usually an absolute path; can be ":memory:" too + return sa_engine.url.database or "records.db" + except Exception: + pass + return "records.db" + + +def _connect_ro() -> sqlite3.Connection: + """Open read-only SQLite with a progress handler timeout.""" + db_file = _resolve_sqlite_path() + conn = sqlite3.connect(f"file:{db_file}?mode=ro", uri=True, check_same_thread=False) + conn.row_factory = sqlite3.Row + start = time.time() + + def progress(): + # abort long-running statements (simple protection) + if time.time() - start > QUERY_TIMEOUT_SECS: + return 1 + return 0 + + conn.set_progress_handler(progress, 10000) + return conn + + +def _assert_select_only(sql: str): + if not SELECT_LIKE.match(sql or ""): + abort(400, "Only SELECT/WITH queries are allowed.") + if ";" in sql: + abort(400, "Semicolons are not allowed.") + + +def _columns_from_query(conn: sqlite3.Connection, base_query: str) -> List[str]: + cur = conn.execute(f"SELECT * FROM ({base_query}) AS t LIMIT 0") + return [d[0] for d in cur.description] + + +def _total_from_query(conn: sqlite3.Connection, base_query: str) -> int: + return int(conn.execute(f"SELECT COUNT(*) AS n FROM ({base_query}) AS sub").fetchone()[0]) + + +def _sorted_query(base_query: str, sort_by: Optional[str], sort_dir: Optional[str], valid_cols: List[str]) -> str: + if not sort_by or not sort_dir: + return f"SELECT * FROM ({base_query}) AS t" + # very basic identifier guard + must be a column from the result set + if not IDENT.fullmatch(sort_by) or sort_by not in valid_cols: + return f"SELECT * FROM ({base_query}) AS t" + dir_sql = "ASC" if sort_dir.lower() == "asc" else "DESC" + return f"SELECT * FROM ({base_query}) AS t ORDER BY \"{sort_by}\" {dir_sql}" + + +@blueprint_sql.post("/api/sql") +def api_sql(): + """ + Body: { query, page, pageSize, sortBy, sortDir } + Returns: { columns: [{field, headerName}], rows: [dict], total: int } + """ + data = request.get_json(force=True, silent=False) or {} + query = (data.get("query") or "").strip() + page = int(data.get("page") or 0) + page_size_req = int(data.get("pageSize") or 25) + sort_by = data.get("sortBy") + sort_dir = data.get("sortDir") + + _assert_select_only(query) + + page_size = min(page_size_req, MAX_PAGE_SIZE) + offset = page * page_size + + try: + conn = _connect_ro() + cols = _columns_from_query(conn, query) + total = _total_from_query(conn, query) + sql_sorted = _sorted_query(query, sort_by, sort_dir, cols) + rows = conn.execute(f"{sql_sorted} LIMIT ? OFFSET ?", (page_size, offset)).fetchall() + except sqlite3.Error as e: + abort(400, f"Query failed: {e}") + finally: + try: + conn.close() + except Exception: + pass + + return jsonify({ + "columns": [{"field": c, "headerName": c} for c in cols], + "rows": [{k: r[k] for k in r.keys()} for r in rows], + "total": int(total), + }) + + +@blueprint_sql.post("/api/sql/export") +def api_sql_export(): + """ + Server-side export. + Body: { query, sortBy, sortDir, format: 'csv'|'tsv' } + Returns: streamed CSV/TSV with up to MAX_EXPORT_ROWS rows. + """ + data = request.get_json(force=True, silent=False) or {} + query = (data.get("query") or "").strip() + sort_by = data.get("sortBy") + sort_dir = data.get("sortDir") + fmt = (data.get("format") or "csv").lower() + delim = "," if fmt == "csv" else "\t" + mime = "text/csv" if fmt == "csv" else "text/tab-separated-values" + + _assert_select_only(query) + + try: + conn = _connect_ro() + cols = _columns_from_query(conn, query) + sql_sorted = _sorted_query(query, sort_by, sort_dir, cols) + cur = conn.execute(f"{sql_sorted} LIMIT ?", (MAX_EXPORT_ROWS,)) + colnames = cols + + def generate(): + # header + yield delim.join(colnames) + "\n" + for row in cur: + vals = [] + for c in colnames: + v = row[c] + if v is None: + vals.append("") + else: + s = str(v).replace("\r", " ").replace("\n", " ") + if delim == "," and ("," in s or '"' in s): + s = '"' + s.replace('"', '""') + '"' + vals.append(s) + yield delim.join(vals) + "\n" + + return Response( + generate(), + mimetype=mime, + headers={"Content-Disposition": f'attachment; filename="export.{fmt}"'}, + ) + except sqlite3.Error as e: + abort(400, f"Export failed: {e}") + finally: + try: + conn.close() + except Exception: + pass From 459ebdaad3615dc0ce76ce43edb0a6fcd04406a1 Mon Sep 17 00:00:00 2001 From: David Meijer Date: Mon, 6 Oct 2025 20:34:47 +0200 Subject: [PATCH 65/65] FIX: corrected query for retrieving entries with signature --- app/src/client/src/pages/query_database.js | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/app/src/client/src/pages/query_database.js b/app/src/client/src/pages/query_database.js index 49bd593..fcab4c8 100644 --- a/app/src/client/src/pages/query_database.js +++ b/app/src/client/src/pages/query_database.js @@ -157,13 +157,13 @@ const QUERYOPTIONS = [ SELECT d.id AS domain_id, p.id AS protein_id, - group_concat(ps.synonym, ', ') AS protein_synonyms + group_concat(ps.synonym, ', ') AS protein_synonyms, pda.domain_number, ad.signature, ad.extended_signature, s.name AS substrate_name, s.smiles AS substrate_smiles, - d.hamming, + d.hamming FROM d JOIN adenylation_domain ad ON ad.id = d.id JOIN protein_domain_association pda ON pda.domain_id = ad.id