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Research PaperResearchia:202601.23011

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

Linhui Xie

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 develop...

Submitted: January 23, 2026Subjects: Biochemistry; Biomolecules

Description / Details

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.


Source: arXiv:2601.17138v2 - http://arxiv.org/abs/2601.17138v2 PDF: https://arxiv.org/pdf/2601.17138v2 Original Link: http://arxiv.org/abs/2601.17138v2

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Submission Info
Date:
Jan 23, 2026
Topic:
Biomolecules
Area:
Biochemistry
Comments:
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