DocumentCode
3310553
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
Volume
3
fYear
2011
fDate
26-28 July 2011
Firstpage
1588
Lastpage
1591
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Systems and Knowledge Discovery (FSKD), 2011 Eighth International Conference on
Conference_Location
Shanghai
Print_ISBN
978-1-61284-180-9
Type
conf
DOI
10.1109/FSKD.2011.6019854
Filename
6019854
Link To Document