title: EPMLR: sequence-based linear B-cell epitope prediction method using multiple linear regression.
abstract: BACKGROUND
  B-cell epitopes have been studied extensively due to their immunological applications, such as peptide-based vaccine development, antibody production, and disease diagnosis and therapy. Despite several decades of research, the accurate prediction of linear B-cell epitopes has remained a challenging task.
  
  
  RESULTS
  In this work, based on the antigen's primary sequence information, a novel linear B-cell epitope prediction model was developed using the multiple linear regression (MLR). A 10-fold cross-validation test on a large non-redundant dataset was performed to evaluate the performance of our model. To alleviate the problem caused by the noise of negative dataset, 300 experiments utilizing 300 sub-datasets were performed. We achieved overall sensitivity of 81.8%, precision of 64.1% and area under the receiver operating characteristic curve (AUC) of 0.728.
  
  
  CONCLUSIONS
  We have presented a reliable method for the identification of linear B cell epitope using antigen's primary sequence information. Moreover, a web server EPMLR has been developed for linear B-cell epitope prediction: http://www.bioinfo.tsinghua.edu.cn/epitope/EPMLR/ .
authors.affiliation: The Key Laboratory of Bioinformatics, Ministry of Education, School of Life Sciences, Tsinghua University, Beijing, 100084, China. lianyao1112@gmail.com.
authors.forename: Yao
authors.initials: Y
authors.lastname: Lian
authors.affiliation: CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China. gemeng@big.ac.cn.
authors.forename: Meng
authors.initials: M
authors.lastname: Ge
authors.affiliation: The Key Laboratory of Bioinformatics, Ministry of Education, School of Life Sciences, Tsinghua University, Beijing, 100084, China. pan-xm@mail.tsinghua.edu.cn.
authors.forename: Xian-Ming
authors.initials: XM
authors.lastname: Pan
mesh_terms: D000465:Algorithms; D001402:B-Lymphocytes / Q000737:chemistry* / Q000276:immunology; D035843:Biomedical Research; D019295:Computational Biology / Q000379:methods*; D018604:Epitope Mapping / Q000379:methods; D018985:Epitopes, B-Lymphocyte / Q000737:chemistry* / Q000276:immunology; D006801:Humans; D016014:Linear Models; D012372:ROC Curve
chemical_list: D018985:Epitopes, B-Lymphocyte