title: Computational prediction of B cell epitopes from antigen sequences.
abstract: Computational identification of B-cell epitopes from antigen chains is a difficult and actively pursued research topic. Efforts towards the development of method for the prediction of linear epitopes span over the last three decades, while only recently several predictors of conformational epitopes were released. We review a comprehensive set of 13 recent approaches that predict linear and 4 methods that predict conformational B-cell epitopes from the antigen sequences. We introduce several databases of B-cell epitopes, since the availability of the corresponding data is at the heart of the development and validation of computational predictors. We also offer practical insights concerning the use and availability of these B-cell epitope predictors, and motivate and discuss feature research in this area.
authors.affiliation: School of Mathematical Sciences, Nankai University, Tianjin, People's Republic of China.
authors.forename: Jianzhao
authors.initials: J
authors.lastname: Gao
authors.forename: Lukasz
authors.initials: L
authors.lastname: Kurgan
mesh_terms: D000818:Animals; D000941:Antigens / Q000737:chemistry* / Q000276:immunology*; D019295:Computational Biology / Q000379:methods*; D066264:Datasets as Topic; D018985:Epitopes, B-Lymphocyte / Q000737:chemistry / Q000276:immunology*; D006801:Humans; D011487:Protein Conformation
chemical_list: D000941:Antigens; D018985:Epitopes, B-Lymphocyte