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The Computational Prediction Methods for Linear B-cell Epitopes

[ Vol. 14 , Issue. 3 ]

Author(s):

Cangzhi Jia*, Hongyan Gong, Yan Zhu and Yixia Shi   Pages 226 - 233 ( 8 )

Abstract:


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.

Keywords:

linear B-cell epitopes, machine learning, bioinformatics, computational, immunological, feature extraction.

Affiliation:

School of Science, Dalian Maritime University, No. 1 Linghai Road, Dalian 116026, School of Science, Dalian Maritime University, No. 1 Linghai Road, Dalian 116026, School of Science, Dalian Maritime University, No. 1 Linghai Road, Dalian 116026, Department of Mathematics and Statistics, Lingnan Normal University, Zhanjiang

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