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J Immunol Methods. 2013 Dec 31;400-401:30-6. doi: 10.1016/j.jim.2013.10.003. Epub 2013 Oct 18.

MHC-NP: predicting peptides naturally processed by the MHC.

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  • 1Department of Computer Science and Software Engineering, Pavillon Adrien-Pouliot, 1065, av. De la Médecine, Université Laval, Québec, Québec, G1V 0A6, Canada. Electronic address: sebastien.giguere.8@ulaval.ca.

Abstract

We present MHC-NP, a tool for predicting peptides naturally processed by the MHC pathway. The method was part of the 2nd Machine Learning Competition in Immunology and yielded state-of-the-art accuracy for the prediction of peptides eluted from human HLA-A*02:01, HLA-B*07:02, HLA-B*35:01, HLA-B*44:03, HLA-B*53:01, HLA-B*57:01 and mouse H2-D(b) and H2-K(b) MHC molecules. We briefly explain the theory and motivations that have led to developing this tool. General applicability in the field of immunology and specifically epitope-based vaccine are expected. Our tool is freely available online and hosted by the Immune Epitope Database at http://tools.immuneepitope.org/mhcnp/.

© 2013.

KEYWORDS:

Epitope; Immunology; Kernel; MHC; Machine learning; Vaccinology

PMID:
24144535
[PubMed - indexed for MEDLINE]
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