title: SVMHC: a server for prediction of MHC-binding peptides.
abstract: Identification of MHC-binding peptides is a prerequisite in rational design of T-cell based peptide vaccines. During the past decade a number of computational approaches have been introduced for the prediction of MHC-binding peptides, efficiently reducing the number of candidate binders that need to be experimentally verified. Here the SVMHC server for prediction of both MHC class I and class II binding peptides is presented. SVMHC offers fast analysis of a wide range of alleles and prediction results are given in several comprehensive formats. The server can be used to find the most likely binders in a protein sequence and to investigate the effects of single nucleotide polymorphisms in terms of MHC-peptide binding. The SVMHC server is accessible at http://www-bs.informatik.uni-tuebingen.de/SVMHC/.
authors.affiliation: Division for Simulation of Biological Systems, WSI/ZBIT, Eberhard Karls University, Tübingen Sand 14, D-72076 Tübingen, Germany. doennes@informatik.uni-tuebingen.de
authors.forename: Pierre
authors.initials: P
authors.lastname: Dönnes
authors.forename: Oliver
authors.initials: O
authors.lastname: Kohlbacher
mesh_terms: D000483:Alleles; D000818:Animals; D001185:Artificial Intelligence; D006649:Histocompatibility Antigens / Q000737:chemistry* / Q000235:genetics; D006801:Humans; D020407:Internet; D051379:Mice; D010455:Peptides / Q000737:chemistry* / Q000235:genetics / Q000276:immunology*; D020641:Polymorphism, Single Nucleotide; D020539:Sequence Analysis, Protein; D012984:Software
chemical_list: D006649:Histocompatibility Antigens; D010455:Peptides