Bioinformatics analysis of rheumatoid arthritis using GEO datasets to identify DEGs, hub genes, and enriched pathways through PPI network and enrichment analysis.

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.

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.