B-EPIC: A Transformer-Based Language Model for Decoding B Cell Immunodominance Patterns.

ABSTRACT: Vaccine development for pathogens has faced significant challenges, contributing to a public health burden. B-cell epitope (BCE) prediction is a crucial process in vaccine development, but is hindered by limited efficiency and accuracy. To address this, B-Epic, the first pipeline applying Transformer to predict BCEs is independently developed. B-Epic's robustness is validated through multiple testing datasets, including distinguishing clinically-approved vaccine targets, identifying BCEs (the Immune Epitope Database testing dataset; n = 23,888) and immunoreactive peptides (Trypanosoma cruzi peptidome; n = 239,575) with high AUCs of 0.882 and 0.945, respectively, outperforming widely used tools. Based on its superior performance, B-Epic is applied to the prevention of carcinogenic pathogens

SUBMITTER: Liang JZ 

PROVIDER: S-EPMC12713022 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature