Artificial neural network based B-cell epitope prediction server

B-cell and epitope of antigen

Recurrent neural network

The aim of ABCpred server is to predict linear B cell epitope regions in an antigen sequence, using artificial neural network. This server will assist in locating epitope regions that are useful in selecting synthetic vaccine candidates, disease diagonosis and also in allergy research.
ABCpred has been trained on B cell epitopes obtained from Bcipep database (BCIPEP), and will therefore presumbly have better performance for prediction of B cell epitope of an antigen. This server can predict continuous (linear) B cell epitopes. A linear B cell epitope is a short peptide that cross-reacts with an antibody, which binds to a conformational epitope.
Users can select window length of 10, 12, 14, 16 and 20 as predicted epitope length. It presents the results in graphical and tabular frame. In case of graphical frame, this server plot the epitopes in blue color along protein backbone (black color), which assist the users in rapid visulaziation of B-cell epitope on protein. The tabular output is in the form of a table, which will provide the aminoacids length from N-terminal to C-terminal in a protein predicted by the server.
The server is able to predict epitopes with 65.93% accuracy using recurrent neural network.
Please cite following paper if you are using ABCpred server
Contact :  G.P.S. Raghava
Bioinformatics Centre
Institute of Microbial Technology,India