Computational Cancer Genomics | Bioinformatics | Python · R · SQL
I'm a Biology graduate and Computer Science student based in Kashiwa, Japan, working at the intersection of machine learning and cancer genomics. I build interpretable ML pipelines and integrate multi-omics data (expression, methylation) on public cancer datasets, with an emphasis on honest, leakage-safe analysis.
- Languages: Python, R, SQL
- Libraries: pandas, NumPy, scikit-learn, Matplotlib, Seaborn, REMP/Bioconductor
- Tools: Git, Jupyter Notebook, Galaxy, SQLite, GDC/TCGA APIs
- Domains: Cancer Genomics, Multi-Omics Integration, NGS Data Analysis, Machine Learning
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🧬 LINE-1 Cancer Atlas (LUAD) — Integrated atlas combining published LINE-1 expression with independently-computed LINE-1 methylation (REMP, TCGA-LUAD) across 468 patients. Finds a significant methylation-expression correlation and a TP53-stratified result extending the published source study.
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🫁 LUAD Recurrence Prediction — Interpretable ML investigation of whether tumor gene expression predicts lung adenocarcinoma progression (TCGA-LUAD). A rigorous, leakage-controlled pipeline and an honest negative result, with a clinical-feature comparison.
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🦟 Philippine Dengue Surveillance Analysis — 6-year DOH dataset analysis identifying outbreak patterns using Python and pandas.
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📊 Superstore Sales Analysis — SQL analysis of 9,994 retail transactions identifying profitability drivers and regional performance gaps.
- Genomac International Cancer Genomics Internship
- BS Computer Science @ Southern New Hampshire University (2027)
- Preparing for graduate study in computational cancer genomics
📍 Kashiwa, Japan · Open to remote opportunities 📧 hirokong20@gmail.com