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

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 ofte...

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Bibliographic Details

Published in:	Bioinformatics (Oxford, England) Vol. 31; no. 22; pp. 3600 - 3607
Main Authors:	Kuksa, Pavel P., Min, Martin Renqiang, Dugar, Rishabh, Gerstein, Mark
Format:	Journal Article
Language:	English
Published:	England 15.11.2015
Subjects:	Algorithms Amino Acid Sequence Area Under Curve Databases, Protein Epitopes - chemistry Humans Major Histocompatibility Complex Molecular Sequence Data Neural Networks (Computer) Peptides - chemistry Peptides - metabolism Protein Binding ROC Curve Support Vector Machine
ISSN:	1367-4803, 1367-4811, 1367-4811
Online Access:	Get full text
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