iLBE for Computational Identification of Linear B-cell Epitopes by Integrating Sequence and Evolutionary Features

作     者：Md.Mehedi Hasan Mst.Shamima Khatun Hiroyuki Kurata Md.Mehedi Hasan;Mst.Shamima Khatun;Hiroyuki Kurata

作者机构：Department of Bioscience and BioinformaticsKyushu Institute of TechnologyIizukaFukuoka 820-8502Japan Biomedical Informatics R&D CenterKyushu Institute of TechnologyIizukaFukuoka 820-8502Japan 

出 版 物：《Genomics, Proteomics & Bioinformatics》 (基因组蛋白质组与生物信息学报（英文版）)

年 卷 期：2020年第18卷第5期

页      面：593-600页

核心收录：

学科分类：0831[工学-生物医学工程（可授工学、理学、医学学位）] 0711[理学-系统科学] 07[理学] 1001[医学-基础医学(可授医学、理学学位)] 08[工学] 100102[医学-免疫学] 10[医学] 

基　　金：supported by the Grant-in-Aid for Challenging Exploratory Research with Japan Society of Promotion of Science(Grant No.17K20009) partially supported by the Ministry of Economy,Trade and Industry,Japan(METI) the Japan Agency for Medical Research and Development(AMED) 

主　　题：Linear B-cell epitope BLAST Feature encoding Feature selection Random forest 

摘      要：Linear B-cell epitopes are critically important for immunological applications,such as vaccine design,immunodiagnostic test,and antibody production,as well as disease diagnosis and *** accurate identification of linear B-cell epitopes remains challenging despite several decades of *** this work,we have developed a novel predictor,Identification of Linear B-cell Epitope(i LBE),by integrating evolutionary and sequence-based *** successive feature vectors were optimized by a Wilcoxon-rank sum *** the random forest(RF)algorithm using the optimal consecutive feature vectors was applied to predict linear B-cell *** combined the RF scores by the logistic regression to enhance the prediction *** yielded an area under curve score of 0.809 on the training dataset and outperformed other prediction models on a comprehensive independent *** is a powerful computational tool to identify the linear B-cell epitopes and would help to develop penetrating diagnostic tests.A web application with curated datasets for iLBE is freely accessible at http://***/iLBE/.