Biomedical scientist and data scientist with 7+ years of experience in single-cell RNA-seq, multi-omics integration, and a growing focus on AI in healthcare. I build scalable, reproducible pipelines and turn complex omics data into actionable insights.
🔬 Expertise: scRNA-seq • Trajectory Inference • Gene Regulation • SCENIC • Network Biology • Spatial Transcriptomics
📦 Tools: R • Python • Bioconductor • GitHub Actions • Singularity • AWS
🧠 Interests: AI in biology • Disease modeling • Translational bioinformatics
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📊 miEdgeR
R package for mutual information-based gene regulatory network inference, hypergraph module detection, and pseudotime-aware analysis of single-cell RNA-seq data. -
🧬 NGS Pipelines
Pipelines for RNA-seq, ChIP-seq, and QC workflows. Includes STAR, Bowtie2, featureCounts, and bamCoverage tools. -
🎯 Neoantigen Detection Pipeline
WES + RNA-seq pipeline for tumor neoantigen discovery using paired tumor-normal data. Includes variant calling, HLA typing, epitope prediction, and prioritization. -
🖥️ RNA-seq Shiny App
Browser-based RNA-seq analysis app with interactive differential expression, gene-level statistics, and visualization. -
🖥️ scRNA-seq Shiny App
Full-featured Shiny tool for single-cell analysis: QC, clustering, annotation, and marker discovery — no coding required.