Computational identification of B- and T-cell epitopes: a unified task taxonomy and review of databases, datasets, predictive pipelines, and gaps.

ABSTRACT: The immune system leverages B and T cells to recognize specific molecular patterns, known as epitopes, on pathogens and cancer cells to effectively combat infections and diseases. The critical success of immunotherapies in cancer treatment and COVID-19 vaccine development has established precise epitope identification as a central and rapidly growing priority in therapeutic design. Because traditional wet-lab based identification of B- and T-cell epitopes is expensive and timeconsuming, our systematic literature search (2015-2026) identified 148 Artificial Intelligence (AI) based linear B-cell, conformational B-cell, and T-cell epitope prediction models within the stated search scope. However, the true potential of these models remains unclear due to fragmented evaluation practices, with m

SUBMITTER: Ibrahim MA 

PROVIDER: S-EPMC13628299 | biostudies-literature | 2026

REPOSITORIES: biostudies-literature