What I do.
For techies: I analyze raw biological sequencing data such RNA-seq, miRNA-seq, 16S rRNA and turn raw reads into something readable and meaningful, mainly to identify biomarkers, molecular pathways, unravel complexities and build reproducible computational workflows.
For non-techies: Every cell, microorgan and microorganism in our body contains an incredible amount of information. With the help of computers and data analysis tools, I find clues to understand and obtain important information regarding human health and disease/disorder development.
Skills
Bioinformatics & Data Analysis
Bulk RNA-seq, miRNA-seq, 16S rRNA via QIIME2 (α/β diversity, taxonomy, PERMANOVA), DESeq2, GSEA, STAR / HISAT2
Computational Tools
Python (EDA, preprocessing, visualisation), R (DESeq2, data wrangling), Bash scripting, Git & GitHub, Galaxy
Research & Communication
Scientific writing, technical writing, documentation, reproducible workflows, written and verbal communication
Projects
Schizophrenia Exosomal miRNA Biomarker Pipeline
End-to-end pipeline for biomarker discovery in first-episode schizophrenia — DESeq2, Random Forest, LASSO, PPI network, GO/KEGG enrichment on GEO data.
View on GitHub → Resources · BioinformaticsBioinformatics Learning Resources
Hand-picked free resources for anyone starting out — Linux basics to RNA-seq and ML for biology.
View on GitHub → ML · Python · SVMDiabetes Prediction using ML
SVM classification on clinical diabetes data — preprocessing, model training, evaluation.
View on GitHub → EDA · PythonHospital Readmission EDA
Exploratory analysis on readmission data — patterns, distributions, and potential predictors.
View on GitHub →Gallery
Conferences & Presentations
