Bioinformatics analysis of rheumatoid arthritis using GEO datasets to identify DEGs, hub genes, and enriched pathways through PPI network and enrichment analysis.
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Updated
Jun 15, 2025
Bioinformatics analysis of rheumatoid arthritis using GEO datasets to identify DEGs, hub genes, and enriched pathways through PPI network and enrichment analysis.
Transparent statistical pipeline for identifying biomarkers associated with neurological disease progression. Spearman correlations, Mann-Whitney group comparisons, volcano plots, and FDR correction.
Multi-omics bioinformatics study investigating XIST as a potential biomarker in breast cancer.
Machine Learning model for predicting ovarian tumor malignancy (benign vs malignant) using clinical biomarkers. Achieves 94% accuracy with Random Forest.
[ISCC, 2026] Official Implementation of "A Quantitative Analysis of Multimodal Biomarkers in Alzheimer's Disease"
PDAC Diagnostic System: Applied ML system for early PDAC detection using urinary biomarkers (LYVE1, REG1B, TFF1). Features a Random Forest classifier, automated biochemical normalization, and PDF clinical reporting. Based on Debernardi et al. (2020) research.
MRI biomarker analysis scripts from MSc Clinical Neuroscience dissertation, UCL
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