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YearIMPACT-FACTOR
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2017  0,977
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2006  0,330
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2003  0,567
2002  0,641
2001  0,490
2000  0,477
1999  0,762
1998  0,785
1997  0,507
1996  0,518
1995  0,502
Vol 43(2009) N 1 p. 150-158;
Ya.I. Davydov, A.G. Tonevitsky

Prediction of linear B-cell epitopes

Faculty of Biology, Moscow State University, Moscow, 119991, Russia
Received - 2008-04-30; Accepted - 2008-06-30

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/.

B-cell epitope prediction, machine learning



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