Record Details

Prediction of continuous B-cell epitopes in an antigen using recurrent neural network.

DIR@IMTECH: CSIR-Institute of Microbial Technology

View Archive Info
 
 
Field Value
 
Title Prediction of continuous B-cell epitopes in an antigen using recurrent neural network.
 
Creator Saha, Sudipto
Raghava, G.P.S.
 
Subject QR Microbiology
 
Description B-cell epitopes play a vital role in the development of peptide vaccines, in diagnosis of diseases, and also for allergy research. Experimental methods used for characterizing epitopes are time consuming and demand large resources. The availability of epitope prediction method(s) can rapidly aid experimenters in simplifying this problem. The standard feed-forward (FNN) and recurrent neural network (RNN) have been used in this study for predicting B-cell epitopes in an antigenic sequence. The networks have been trained and tested on a clean data set, which consists of 700 non-redundant B-cell epitopes obtained from Bcipep database and equal number of non-epitopes obtained randomly from Swiss-Prot database. The networks have been trained and tested at different input window length and hidden units. Maximum accuracy has been obtained using recurrent neural network (Jordan network) with a single hidden layer of 35 hidden units for window length of 16. The final network yields an overall prediction accuracy of 65.93% when tested by fivefold cross-validation. The corresponding sensitivity, specificity, and positive prediction values are 67.14, 64.71, and 65.61%, respectively. It has been observed that RNN (JE) was more successful than FNN in the prediction of B-cell epitopes. The length of the peptide is also important in the prediction of B-cell epitopes from antigenic sequences. The webserver ABCpred is freely available at www.imtech.res.in/raghava/abcpred/.
 
Publisher Wiley
 
Date 2006-10-01
 
Type Article
PeerReviewed
 
Format application/pdf
 
Identifier http://crdd.osdd.net/open/140/1/raghava2006.3.pdf
Saha, Sudipto and Raghava, G.P.S. (2006) Prediction of continuous B-cell epitopes in an antigen using recurrent neural network. Proteins, 65 (1). pp. 40-8. ISSN 1097-0134
 
Relation http://onlinelibrary.wiley.com/doi/10.1002/prot.21078/pdf
http://crdd.osdd.net/open/140/