BepiTBR

A prediction model that leverages T-B reciprocity to enhance B cell epitopes prediction
online analysis

Introduction


The ability to predict B cell epitopes from antigen sequences is critical for biomedical research and many clinical applications. However, despite substantial efforts over the past 20 years, the performance of even the best B cell epitope prediction software is still modest. Based on the idea of T-B reciprocity, BepiTBR is a B cell epitope prediction model that demonstrates improved performance by incorporating prediction of nearby CD4+ T cell epitopes close to the B cell epitopes.


Author


:   James Zhu

:   James.Zhu@UTSouthwestern.edu

:   GitHub

Citation


If you use BepiTBR in your publication, please cite the following paper:

"Zhu, James et al. (2022) BepiTBR: T-B reciprocity enhances B cell epitope prediction. iScience, Volume 25, Issue 2, 103764"