TCR embedding expressivity evaluation framework.
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Updated
Jan 1, 2025 - Python
TCR embedding expressivity evaluation framework.
About me (Soumya Banerjee)
Curriculum Vitae
A Mathematical and Computational Model for simulating immune regulation of Type 1 Diabetes.
Computational pipeline for antigen-specific tolerogenic vaccine design—predicting MHC-II epitopes, scoring tolerance potential, and assembling candidate multi-epitope mRNA constructs (starting with ITP).
A multi-language bioinformatics pipeline (Bash, R, Python) for single-cell RNA-seq analysis of the Melanoma tumor microenvironment. Identifies CD8+ T-cell exhaustion signatures and statistically validates them as predictive biomarkers for Immune Checkpoint Blockade (ICB) therapy response.
End-to-end clinical shotgun metagenomic pipeline investigating microbial triggers (NOD2/TLR4) of metabolic inflammation, disproving barrier failure and supporting the Host Autonomy model in Type 2 Diabetes.
TCR-Epitope-MHC Binding Prediction with Metric Learning
MacroImmunet is a modular, event-driven research demo for agent-based simulation of immune responses at the tissue / organ scale. Rather than reproducing full single-cell biophysics, it explores how immune behavior emerges from structured coordination layers acting over spatial fields.
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