title: BiodMHC: an online server for the prediction of MHC class II-peptide binding affinity.
abstract: Effective identification of major histocompatibility complex (MHC) molecules restricted peptides is a critical step in discovering immune epitopes. Although many online servers have been built to predict class II MHC-peptide binding affinity, they have been trained on different datasets, and thus fail in providing a unified comparison of various methods. In this paper, we present our implementation of seven popular predictive methods, namely SMM-align, ARB, SVR-pairwise, Gibbs sampler, ProPred, LP-top2, and MHCPred, on a single web server named BiodMHC (http://biod.whu.edu.cn/BiodMHC/index.html, the software is available upon request). Using a standard measure of AUC (Area Under the receiver operating characteristic Curves), we compare these methods by means of not only cross validation but also prediction on independent test datasets. We find that SMM-align, ProPred, SVR-pairwise, ARB, and Gibbs sampler are the five best-performing methods. For the binding affinity prediction of class II MHC-peptide, BiodMHC provides a convenient online platform for researchers to obtain binding information simultaneously using various methods.
authors.affiliation: School of Computer, Wuhan University, Wuhan 430079, China.
authors.forename: Lian
authors.initials: L
authors.lastname: Wang
authors.forename: Danling
authors.initials: D
authors.lastname: Pan
authors.forename: Xihao
authors.initials: X
authors.lastname: Hu
authors.forename: Jinyu
authors.initials: J
authors.lastname: Xiao
authors.forename: Yangyang
authors.initials: Y
authors.lastname: Gao
authors.forename: Huifang
authors.initials: H
authors.lastname: Zhang
authors.forename: Yan
authors.initials: Y
authors.lastname: Zhang
authors.forename: Juan
authors.initials: J
authors.lastname: Liu
authors.forename: Shanfeng
authors.initials: S
authors.lastname: Zhu
mesh_terms: D000818:Animals; D030562:Databases, Protein; D000949:Histocompatibility Antigens Class II / Q000737:chemistry* / Q000378:metabolism*; D006801:Humans; D020407:Internet; D009862:Online Systems; D010455:Peptides / Q000737:chemistry / Q000378:metabolism; D011485:Protein Binding; D012984:Software
chemical_list: D000949:Histocompatibility Antigens Class II; D010455:Peptides