I'm a scientist transitioning into translational data science — using biological intuition from the lab to design, analyse, and interpret data-driven experiments.
My goal is to bridge wet-lab expertise with computational analysis to answer questions that matter in cancer biology, immunology, and drug discovery.
- Trained in immunology and cancer biology
- Experience with TCR-based therapies, tumour invasion models, and target discovery
- Currently building reproducible, shareable analyses for projects I've worked on
| Project | Description | Status |
|---|---|---|
| Flow Cytometry Analysis | Computational analysis of flow data using R/Python | 🔄 In progress |
| Gene Expression & Survival (RTCGA) | Comparing gene expression with patient survival curves in cancer datasets | 🔄 In progress |
| 3D Invasion Assay Analysis | Quantitative image/data analysis of tumour invasion models with Python | 🔄 In progress |
| TCR-seq & scRNA-seq | Immune repertoire and single-cell transcriptomics (reproducing with public data) | 📅 Planned |
| Phage Display Target Discovery | Data analysis pipeline for TCR therapy target identification | 📅 Planned |
| PGV001 Neoantigen Pipeline | Neoantigen prediction pipeline analysis and reporting | 📅 Planned |
Languages
Bioinformatics & Analysis
- Single-cell RNA-seq · TCR-seq · Flow cytometry
- Survival analysis · Gene expression · Neoantigen prediction
- Image analysis · Phage display data
Frameworks & Packages
- R:
Bioconductor,RTCGA,survival,ggplot2,Seurat - Python:
pandas,numpy,scikit-image,matplotlib,scanpy
Feel free to reach out if you're working on something at the intersection of immunology, cancer biology, and data science.
This profile is a work in progress — repositories are being added as analyses are completed and documented. 🚧