Prediction of linear B-cell epitopes

被引：20

作者：

Davydov, Ya. I. ^{[1
]}

Tonevitsky, A. G. ^{[1
]}

机构：

[1] Moscow MV Lomonosov State Univ, Fac Biol, Moscow 119991, Russia

来源：

MOLECULAR BIOLOGY | 2009年 / 43卷 / 01期

关键词：

B-cell epitope prediction; machine learning; ANTIGENIC DETERMINANTS; RESIDUES; LOCATION; DATABASE; JENPEP;

D O I：

10.1134/S0026893309010208

中图分类号：

Q5 [生物化学]; Q7 [分子生物学];

学科分类号：

071010 ; 081704 ;

摘要：

The use of antigenicity scales based on physicochemical properties and the sliding window method in combination with an averaging algorithm and subsequent search for the maximum value is the classical method for B-cell epitope prediction. However, recent studies have demonstrated that the best classical methods provide a poor correlation with experimental data. We review both classical and novel algorithms and present our own implementation of the algorithms. The AAPPred software is available at http://www.bioinf.ru/aappred.

引用

页码：150 / 158

页数：9

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