title: T-Cell Epitope Prediction of Chikungunya Virus.
abstract: There has been a growing demand for vaccines against Chikungunya virus (CHIKV), and epitope-based vaccine is a promising solution. Identification of CHIKV T-cell epitopes is critical to ensure successful trigger of immune response for epitope-based vaccine design. Bioinformatics tools are able to significantly reduce time and effort in this process by systematically scanning for immunogenic peptides in CHIKV proteins. This chapter provides the steps in utilizing machine learning algorithms to train on major histocompatibility complex (MHC) class I peptide binding data and build prediction models for the classification of binders and non-binders. The models could then be used in the identification and prediction of CHIKV T-cell epitopes for future vaccine design.
authors.affiliation: Department of Biochemistry, Yong Loo School of Medicine, National University of Singapore, Singapore, 117597, Singapore.
authors.forename: Christine Loan Ping
authors.initials: CL
authors.lastname: Eng
authors.affiliation: Department of Biochemistry, Yong Loo School of Medicine, National University of Singapore, Singapore, 117597, Singapore.
authors.forename: Tin Wee
authors.initials: TW
authors.lastname: Tan
authors.affiliation: Department of Biochemistry, Yong Loo School of Medicine, National University of Singapore, Singapore, 117597, Singapore. victor@bic.nus.edu.sg.|Institute of High Performance Computing, Agency for Science, Technology and Research, 1 Fusionopolis Way, #16-16 Connexis North, Singapore, 138632, Singapore. victor@bic.nus.edu.sg.
authors.forename: Joo Chuan
authors.initials: JC
authors.lastname: Tong
mesh_terms: D000465:Algorithms; D002646:Chikungunya virus / Q000276:immunology*; D019295:Computational Biology / Q000379:methods; D018984:Epitopes, T-Lymphocyte / Q000378:metabolism*; D015395:Histocompatibility Antigens Class I / Q000276:immunology; D000069550:Machine Learning
chemical_list: D018984:Epitopes, T-Lymphocyte; D015395:Histocompatibility Antigens Class I
keywords: Antigens; Chikungunya/CHIKV; Epitopes; MHC; Machine learning; Peptides; Prediction