High-order neural networks and kernel methods for peptide-MHC binding prediction

Abstract

MOTIVATION Effective computational methods for peptide-protein binding prediction can greatly help clinical peptide vaccine search and design. However, previous computational methods fail to capture key nonlinear high-order dependencies between different amino acid positions. As a result, they often produce low-quality rankings of strong binding peptides… (More)
DOI: 10.1093/bioinformatics/btv371

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