Thi Kim Cuong Ho

CALFP-MHC improves peptide-MHC binding prediction by using chemically grounded fingerprints and contrastive learning, achieving high AUC and PPV across diverse alleles and class imbalance.

This paper develops a machine learning model that integrates TCRβ and pHLA binding data to improve neoantigen prioritization in colorectal cancer, showing better performance than existing tools.