BEST : improved prediction of B-Cell Epitopes from antigen sequences

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IDL-51226.pdf (592.65 KB)

Date

2012

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Journal Title

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Volume Title

Publisher

PLOS

Abstract

Accurate identification of immunogenic regions in a given antigen chain is a difficult and actively pursued problem. Although accurate predictors for T-cell epitopes are already in place, research on the prediction of B-cell epitopes is ongoing. In this article a new approach for the prediction of B-cell epitopes from antigen sequences is proposed: the ‘BEST’ method predicts epitopes from full protein, based on averaging selected scores generated from 20-mers by a Support Vector Machine (SVM)-based predictor. A comprehensive and custom designed set of inputs is used, generated by fusing information derived from the protein chain.

Description

Keywords

B-LYMPHOCYTES, ANTIGENS, EPITOPES, B-LYMPHOCYTE

Citation

Gao, J. Faraggi, E. Zhou, Y. Ruan, J., & Kurgan, L. (2012). BEST: Improved Prediction of B-Cell Epitopes from Antigen Sequences. PLoS ONE, 7(6), e40104.doi:10.1371/journal.pone.0040104

URI

http://hdl.handle.net/10625/51226
 http://www.plosone.org/article/info:doi/10.1371/journal.pone.0040104

DOI

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IDRC Research Results / Résultats de recherches du CRDI
2010-2019 / Années 2010-2019
Modelling and controlling infectious diseases / Se servir de la modélisation pour lutter contre les maladies infectieuses