title: MHCPred: bringing a quantitative dimension to the online prediction of MHC binding.
abstract: The accurate prediction of T cell epitopes is one of the key aspirations of immunoinformatics. We have developed a partial least squares-based, robust multivariate statistical method for the quantitative prediction of peptide binding to major histocompatibility complexes (MHCs), the principal checkpoint on the antigen presentation pathway. As a service to the immunobiology community, we have made a Perl implementation of the method available as a World Wide Web server.
authors.affiliation: Edward Jenner Institute for Vaccine Research, Berkshire, UK.
authors.forename: Pingping
authors.initials: P
authors.lastname: Guan
authors.forename: Irini A
authors.initials: IA
authors.lastname: Doytchinova
authors.forename: Christianna
authors.initials: C
authors.lastname: Zygouri
authors.forename: Darren R
authors.initials: DR
authors.lastname: Flower
mesh_terms: D000465:Algorithms; D017951:Antigen Presentation; D001665:Binding Sites; D003198:Computer Simulation; D018984:Epitopes, T-Lymphocyte / Q000737:chemistry / Q000276:immunology; D006649:Histocompatibility Antigens / Q000737:chemistry* / Q000276:immunology; D020407:Internet; D008285:Major Histocompatibility Complex; D008956:Models, Chemical; D008958:Models, Molecular; D009862:Online Systems; D010455:Peptides / Q000737:chemistry* / Q000276:immunology; D011485:Protein Binding; D020539:Sequence Analysis, Protein / Q000379:methods*; D012984:Software; D014584:User-Computer Interface
chemical_list: D018984:Epitopes, T-Lymphocyte; D006649:Histocompatibility Antigens; D010455:Peptides