dataset definitions

[cmatKhan]

Write descriptions for each datasets. Note that this text will be added to the huggingface datacard description field for each dataset

[michael-brent]

Notes

Here is some text to use for the binding dataset tool tips. Can also be repeated the Filter modal. Someone else can make text for the perturbation data based on this model and I will edit.

Link the text of the citation to a doi or URL so users can click on it to get to the paper. Then remove the DOI from the textual citation -- not meant for humans to read.

For Harbison
ChIP-chip data, primarily in standard YPD batch culture, but selected TFs were also tested in specific conditions where they were expected to be active.

Publication: Harbison CT, Gordon DB, Lee TI, Rinaldi NJ, Macisaac KD, et al. 2004. Transcriptional regulatory code of a eukaryotic genome. Nature. doi: 10.1038/nature02800. PubMed PMID: 15343339; PMCID: 3006441.

For Rossi
ChIP-exo (a variant of ChIP-seq) data, primarily in YPD batch cultures at 25C. Includes DNA-binding transcription factors and many other chromatin factors.

Publication: Rossi, MJ, Kuntala, PK, Lai, WKM, Yamada, N, Badjatia, N, Mittal, et al. 2021. A high-resolution protein architecture of the budding yeast genome. Nature. doi: 10.1038/s41586-021-03314-8

For Mateusiak
Data generated with calling cards, a method that inserts transposons near TF binding sites, from cells growing on synthetic complete media at room temperature with galactose as the sole carbon source.

Publication: Mateusiak, C, Erdenebaatar, Z, Jia, E, Plaggenberg, JN, Wang, Y, Shively, C, Liao, G, Mitra, RD, Brent, MR. 2026. Functional synergy partially explains why most transcription factor binding is non-functional. bioRxiv: 2026.2001.2019.700460. doi: 10.64898/2026.01.19.700460

For Hughes knockout
?? Chase fill in

For Hughes overexpression
?? Chase fill in*

For Kemmeren
Microarray expression data comparing strains in which the gene encoding a single protein has been deleted. Includes sequence-specific DNA-binding TFs as well kinases, phosphatases, and many other potential regulatory proteins. Cells were grown on synthetic complete medium with glucose.

Publication: Kemmeren, P, Sameith, K, van de Pasch, LA, Benschop, JJ, Lenstra, TL, Margaritis, T, et al. 2014. Large-scale genetic perturbations reveal regulatory networks and an abundance of gene-specific repressors. Cell, 157: 740-752. doi: 10.1016/j.cell.2014.02.054

For Hackett
Microarray expression data comparing cells without estradiol inducer, which express a TF at a very low level and post-induction, which express the TF at a high level by 15-30 minutes post induction. Contains many time points. Cells were grown in minimal medium with glucose in continuous-flow chemostats. In most experiments growth was limited by phosphate limitation.

Publication: Hackett, SR, Baltz, EA, Coram, M, Wranik, BJ, Kim, et al. 2020. Learning causal networks using inducible transcription factors and transcriptome-wide time series. Molecular Systems Biology. doi: 10.15252/msb.20199174

For Degron
?? Chase fill in

[cmatKhan]

@MackLiao , see #240

There will be two fields from the datacard available through the vdb datacard, citation and doi. Citation will be the plain text paper citation, eg

Hackett, SR, Baltz, EA, Coram, M, Wranik, BJ, Kim, et al. 2020. Learning causal networks using inducible transcription factors and transcriptome-wide time series. Molecular Systems Biology.

under dataset title in filter modal

[original paper](doi link)
plain text citation (like the hackett example above) in smaller font

[cmatKhan]

for harbison

ChIP-chip data, primarily in standard YPD batch culture, but selected TFs were also tested in specific conditions where they were expected to be active.

~42% in at least 2 conditions

[michael-brent]

OK, change "selected TFs" to "XX TFs" where XX is the number.

…

On Tue, Apr 21, 2026 at 6:36 PM Chase Mateusiak ***@***.***> wrote: *cmatKhan* left a comment (BrentLab/tfbpshiny#239) <#239 (comment)> for harbison ChIP-chip data, primarily in standard YPD batch culture, but selected TFs were also tested in specific conditions where they were expected to be active. ~42% in at least 2 conditions — Reply to this email directly, view it on GitHub <#239?email_source=notifications&email_token=AONOK2RGS7OBDMDZLAYSW5T4XAAY5A5CNFSNUABFM5UWIORPF5TWS5BNNB2WEL2JONZXKZKDN5WW2ZLOOQXTIMRZGI2TIOJVGA42M4TFMFZW63VGMFZXG2LHN2SWK5TFNZ2KYZTPN52GK4S7MNWGSY3L#issuecomment-4292549509>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AONOK2XZEYBUE256ZPSUMSL4XAAY5AVCNFSM6AAAAACXP33HGWVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHM2DEOJSGU2DSNJQHE> . You are receiving this because you were assigned.Message ID: ***@***.***>