Santrupti Nerli

This study evaluates ML and biophysical models for predicting TCR-pMHC specificity, showing ML struggles with novel peptides while biophysical methods excel but underperform on known ones, leading to a hybrid model with improved performance.

ConformAb designs antibody sequences that maintain CDR canonical conformations, improving binding affinity without target-specific data.

This paper introduces a machine learning framework for therapeutic antibody design that integrates computational methods with experimental validation, resulting in significantly improved binding affinity for multiple targets.

This paper introduces HLA3DB, a curated database of peptide/HLA complexes, and presents RepPred, a method for predicting T cell epitope structures with improved accuracy.

The paper describes a SARS-CoV-2 genome browser that integrates molecular data from multiple sources for visualization and analysis.