RNA-seq bioinformatics pipeline identifying resistance-associated biomarkers and prognostic signatures in TCGA breast cancer transcriptomic data.

RNA-seq analysis workflow using DESeq2

Survival Analysis Project on Breast Cancer Patients

Find tumor gene mutation rates (TP53 and STAT5A) using cancer datasets from The Cancer Genome Atlas.

Relevance of genes on survival in Breast Cancer Patients

We use gene expression data to perform gene set enrichments and random forest predictions to distinguish between four tumor types.

Analyzing TCGA cohorts and multiomic data in R

Hybrid Classical-Quantum ML system for BRCA1/BRCA2 variant classification using ClinVar data.