Epitopedia: identifying molecular mimicry of known immune epitopes
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Updated
Feb 18, 2022 - JavaScript
Epitopedia: identifying molecular mimicry of known immune epitopes
Standalone Python package for annotating protein sequences with biological and physicochemical properties (iFeature, IEDB, SignalP) for reverse vaccinology. Extracted from VacSol-ML(ESKAPE); supports multi-allele MHC-I/II epitope prediction. Provides both a Python API and a CLI
HLA-A*02:01 nine-mer peptide binding prediction from sequence, with grouped validation and fully traceable metrics.
Bias-controlled evaluation protocol and pipeline for neoantigen immunogenicity prediction: matched HLA-only and peptide-only null controls, shortcut-dependence diagnostics, and a no-override acceptance gate.
Comparative evaluation of Machine Learning and Deep Learning models for peptide immunogenicity prediction using physicochemical feature engineering and class imbalance handling.
Chapter 6 of Machine Learning for Biology. Sequence-only immunogenicity prediction on 1,200 HLA-A*02:01 IEDB binders, cluster-split and pre-registered. Network 0.610 AUPRC, binding-only baseline 0.591, chance 0.485.
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