Titlebook: Immunoinformatics; Predicting Immunogen Darren R. Flower Book 2007 Humana Press 2007 Allele.Antigen.Computer.In silico.artificial intellige

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Structural Basis for HLA-A2 Supertypesalleles in a combinatorial manner. However, it has been suggested that majority of alleles can be covered within few HLA supertypes, where different members of a supertype bind similar peptides, yet exhibiting distinct repertoires. Nonetheless, the structural basis for HLA supertype-like function is

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Definition of MHC Supertypes Through Clustering of MHC Peptide-Binding Repertoiresthe design of epitope-based vaccines. Population coverage of epitope vaccines is, however, compromised by the extreme polymorphism of MHC molecules, which is in fact the basis for their differential peptide binding. Therefore, grouping of MHC molecules into supertypes according to peptide-binding sp

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Prediction of Peptide-MHC Binding Using Profiles given MHC molecule are related by sequence similarity. Therefore, a position-specific scoring matrix (PSSM)—also known as profile—derived from a set of aligned peptides known to bind to a given MHC molecule can be used as a predictor of both peptide–MHC binding and T-cell epitopes. In this approach

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Artificial Intelligence Methods for Predicting T-Cell Epitopes diseases and cancers. We have applied two artificial intelligence approaches to build models for predicting T-cell epitopes. We developed a support vector machine to predict T-cell epitopes for an MHC class I-restricted T-cell clone (TCC) using synthesized peptide data. For predicting T-cell epitop

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https://doi.org/10.1007/978-1-60327-118-9Allele; Antigen; Computer; In silico; artificial intelligence; calculus; database; databases; genetics; machi

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Immunoinformatics978-1-60327-118-9Series ISSN 1064-3745 Series E-ISSN 1940-6029