AI Developments for T and B Cell Receptor Modeling and Therapeutic Design

Read full text
Authors: Linhui Xie, Aurélien Pélissier, Yanjun Shao, María Rodríguez Martínez
Cited by: 0

Abstract

Artificial intelligence (AI) is accelerating progress in modeling T and B cell receptors by enabling predictive and generative frameworks grounded in sequence data and immune context. This chapter surveys recent advances in the use of protein language models, machine learning, and multimodal integration for immune receptor modeling. We highlight emerging strategies to leverage single-cell and repertoire-scale datasets, and optimize immune receptor candidates for therapeutic design. These developments point toward a new generation of data-efficient, generalizable, and clinically relevant models that better capture the diversity and complexity of adaptive immunity.

Fields of Study & Subjects

vaccines and immunoinformatics approaches T-cell and B-cell Immunology Machine Learning in Bioinformatics

Publication details

Journal / source
arXiv (Cornell University)
Publication date
23 January 2026
Document type
Preprint