MHC2MIL: a novel multiple instance learning based method for MHC-II peptide binding prediction by considering peptide flanking region and residue positions

摘要

BackgroundComputational prediction of major histocompatibility complex class II (MHC-II) binding peptides can assist researchers in understanding the mechanism of immune systems and developing peptide based vaccines. Although many computational methods have been proposed, the performance of these methods are far from satisfactory. The difficulty of MHC-II peptide binding prediction comes mainly from the large length variation of binding peptides.