Title :
Choquet integral algorithm for T-cell epitope prediction based on fuzzy measure
Author :
Ya-Li Hsiao ; Hsiang-Chuan Liu ; Po-Fon Chen ; Pei-Chun Chang ; Cheng-Fang Tsai
Author_Institution :
Dept. of Bioinf., Asia Univ., Taichung, Taiwan
Abstract :
Epitope is an antigen segment which is recognized by the immune system specifically and induces immune response. To accurately predict epitopes is essential in vaccine design that is one goal of immunoinformatics. In this study, we consider the coupling effects of physicochemical properties in an amino acid with fuzzy theory to improve the prediction accuracy.
Keywords :
biochemistry; bioinformatics; fuzzy set theory; Choquet integral algorithm; T-cell Epitope prediction; amino acid; antigen segment; coupling effect; fuzzy measure; fuzzy theory; immune response; immune system; immunoinformatics goal; physicochemical property; vaccine design; Accuracy; Amino acids; Bioinformatics; Immune system; Peptides; Prediction algorithms; Support vector machines; SVM; T-cell; antigen; epitope; fuzzy integral; fuzzy measure; physicochemical property;
Conference_Titel :
Fuzzy Systems and Knowledge Discovery (FSKD), 2011 Eighth International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-61284-180-9
DOI :
10.1109/FSKD.2011.6019854
