Computational Biologist · Mathematical Modeller · Open-Science Advocate
Transforming biological complexity into computationally tractable problems
I integrate multi-omics data, build optimization-driven models that link molecular networks to drug responses, and develop reproducible open-source pipelines with high-performance computing, containerization, and workflow systems.
My work sits at the intersection of mathematical modelling, systems biology, and precision medicine — where equations and algorithms translate biological noise into clinical insight.
Education
- 🎓 M.Sc. Bioinformatics — Freie Universität Berlin, 2025
- 🎓 B.Tech. Bioinformatics — Jaypee University of Information Technology, 2017
Built and validated an optimization framework to reconstruct phosphorylation signalling networks in triple-negative breast cancer (TNBC) from mass-spectrometry proteomics data.
Python Optimization Proteomics Systems Biology
Developed a mechanistic PBPK model for drug distribution in the human body — parameterised from tissue composition and plasma binding data.
ODE Systems Pharmacokinetics Mathematical Modelling
Designed and tested an end-to-end bioinformatics pipeline for prostate cancer biomarker discovery — integrating gene expression data, differential analysis, and pathway enrichment.
RNA-seq Bioinformatics Pathway Analysis
Engineered a molecular docking workflow to screen FDA-approved compounds against the dopamine D3 receptor for potential repurposing in schizophrenia treatment.
Molecular Docking Drug Repurposing Cheminformatics
| Domain | Tools & Technologies |
|---|---|
| Languages | Python · R · Bash · MATLAB |
| Modelling & Optimisation | ODE systems · Flux Balance Analysis · Constraint-based modelling · PBPK |
| Multi-omics | Proteomics · Transcriptomics · scRNA-seq · Pathway enrichment |
| HPC & Workflow | Snakemake · Nextflow · Singularity · SLURM |
| Data & Viz | Pandas · NumPy · SciPy · Matplotlib · Seaborn · ggplot2 |
| Reproducibility | Docker · Git · Zenodo · GitHub Actions |
Precision Medicine → predictive models for clinical decision support
Mathematical Pharmacology → PK/PD, PBPK, drug-response modelling
Network Biology → signalling networks, phosphoproteomics, graph theory
Multi-omics Integration → data fusion across genomics, proteomics, metabolomics
Open Science → FAIR data, reproducible pipelines, open-source tooling
| Year | Output | Link |
|---|---|---|
| 2025 | Phospho-network reconstruction framework (TNBC) | Zenodo · Code |
| 2025 | PBPK model for human drug distribution | Zenodo |
| 2018 | Prostate cancer biomarker discovery pipeline | J. Integr. Bioinform. |
I'm always glad to collaborate on bioinformatics, computational biology, or open-science projects. Looking ahead, I aim to expand my modelling and integration methods toward precision medicine, where predictive models can guide real-world clinical decisions.
"Mathematics is the language in which biology hides its deepest secrets."