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• W2153268005 abstract "The T-cell receptor, a major histocompatibility complex (MHC) molecule, and a bound antigenic peptide, play major roles in the process of antigen-specific T-cell activation. T-cell recognition was long considered exquisitely specific. Recent data also indicate that it is highly flexible, and one receptor may recognize thousands of different peptides. Deciphering the patterns of peptides that elicit a MHC restricted T-cell response is critical for vaccine development.For the first time we develop a support vector machine (SVM) for T-cell epitope prediction with an MHC type I restricted T-cell clone. Using cross-validation, we demonstrate that SVMs can be trained on relatively small data sets to provide prediction more accurate than those based on previously published methods or on MHC binding.Data for 203 synthesized peptides is available at http://linus.nci.nih.gov/Data/LAU203_Peptide.pdf" @default.
• W2153268005 created "2016-06-24" @default.
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• W2153268005 date "2003-10-12" @default.
• W2153268005 modified "2023-09-26" @default.
• W2153268005 title "Application of support vector machines for T-cell epitopes prediction" @default.
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• W2153268005 doi "https://doi.org/10.1093/bioinformatics/btg255" @default.
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