Decoding life one read at a time — where biology meets code.
I'm a Master's student in Bioinformatics passionate about leveraging computational approaches to unravel the complexity of the genome. My work sits at the intersection of single-cell biology, multi-omics integration, and machine learning.
- Single-Cell RNA Sequencing (scRNA-seq) — Cell type annotation, trajectory inference, differential expression
- Multi-Omics Integration — ATAC-seq, proteomics, spatial transcriptomics
- Genomics & NGS Analysis — Variant calling, genome assembly, read alignment pipelines
- Machine Learning in Biology — Dimensionality reduction, clustering, predictive modeling on omics data
STAR · HISAT2 · BWA · GATK · DESeq2 · edgeR · Salmon · Trimmomatic · FastQC · MultiQC
Scikit-learn · PyTorch · Pandas · Harmony · MOFA+ · ggplot2 · Shiny
| Repository | Description | Stack |
|---|---|---|
🧫 scRNA-pipeline |
End-to-end single-cell RNA-seq analysis pipeline | R · Seurat · Harmony |
🧪 multiomics-integration |
MOFA+-based integration of RNA + ATAC data | Python · R · MOFA+ |
🖥️ omics-shiny-app |
Interactive Shiny app for scRNA-seq visualization | R · Shiny · ggplot2 |
🔩 ngs-workflow |
Reproducible NGS processing with Snakemake | Snakemake · GATK · STAR |
🤖 cell-type-classifier |
ML model for automated cell type classification | Python · Scikit-learn |
"In biology, nothing makes sense except in the light of evolution — and increasingly, in the light of data."