EPSVR and EPMeta: prediction of antigenic epitopes using support vector regression and multiple server results

Background: Accurate prediction of antigenic epitopes is important for immunologic research and medical applications, but it is still an open problem in bioinformatics. The case for discontinuous epitopes is even worse currently there are only a few discontinuous epitope prediction servers available, though discontinuous peptides constitute the majority of all B-cell antigenic epitopes. The small number of structures for antigen-antibody complexes limits the development of reliable discontinuous epitope prediction methods and an unbiased benchmark to evaluate developed methods. Results: In this work, we present two novel server applications for discontinuous epitope prediction: EPSVR and EPMeta, where EPMeta is a meta server. EPSVR, EPMeta, and datasets are available at http://sysbio.unl.edu/services. Conclusion: The server application for discontinuous epitope prediction, EPSVR, uses a Support Vector Regression (SVR) method to integrate six scoring terms. Furthermore, we combined EPS...

• Type: Journal
• Year: 2010
• Where: BMCBI
• Authors: Shide Liang, Dandan Zheng, Daron M. Standley, Bo Yao, Martin Zacharias, Chi Zhang
• Keywords: BMCBI 2010, Discontinuous Epitope, Discontinuous Epitope Prediction, Epitope