Brandon Malone

This study identifies conserved T-cell targets across betacoronaviruses using machine learning and validates their immunogenicity through functional assays and mRNA vaccination in mice.

BERTMHC improves MHC class II peptide binding prediction using a transformer model and multiple instance learning, outperforming existing methods.

The paper introduces dom2vec, a method for learning protein domain embeddings and evaluates their quality using intrinsic strategies, showing they perform well on downstream tasks.

This study uses AI to predict immunogenic epitopes across SARS-CoV-2 variants, identifying vaccine candidates with broad population coverage.

DOUBLER learns unified representations of biological entities and documents to predict protein-disease relationships, outperforming existing methods when additional data modalities are informative.