The Computational Prediction Methods for Linear B-cell Epitopes

被引：3
|
作者：
Jia, Cangzhi [1 ]
Gong, Hongyan [1 ]
Zhu, Yan [1 ]
Shi, Yixia [2 ]
机构：
[1] Dalian Maritime Univ, Sch Sci, 1 Linghai Rd, Dalian 116026, Peoples R China
[2] Lingnan Normal Univ, Dept Math & Stat, Zhanjiang, Peoples R China
来源：
CURRENT BIOINFORMATICS | 2019年 / 14卷 / 03期
关键词：
linear B-cell epitopes; machine learning; bioinformatics; computational; immunological; feature extraction; DATABASE;
D O I：
10.2174/1574893613666181112145706
中图分类号：
Q5 [生物化学];
学科分类号：
071010 ; 081704 ;
摘要：
Background: B-cell epitope prediction is an essential tool for a variety of immunological studies. For identifying such epitopes, several computational predictors have been proposed in the past 10 years. Objective: In this review, we summarized the representative computational approaches developed for the identification of linear B-cell epitopes. Methods: We mainly discuss the datasets, feature extraction methods and classification methods used in the previous work. Results: The performance of the existing methods was not very satisfying, and so more effective approaches should be proposed by considering the structural information of proteins. Conclusion: We consider existing challenges and future perspectives for developing reliable methods for predicting linear B-cell epitopes.
引用
收藏
页码：226 / 233
页数：8
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