English

Large Language Models in Bioinformatics: A Survey

Computation and Language 2026-03-03 v3 Genomics

Abstract

Large Language Models (LLMs) are revolutionizing bioinformatics, enabling advanced analysis of DNA, RNA, proteins, and single-cell data. This survey provides a systematic review of recent advancements, focusing on genomic sequence modeling, RNA structure prediction, protein function inference, and single-cell transcriptomics. Meanwhile, we also discuss several key challenges, including data scarcity, computational complexity, and cross-omics integration, and explore future directions such as multimodal learning, hybrid AI models, and clinical applications. By offering a comprehensive perspective, this paper underscores the transformative potential of LLMs in driving innovations in bioinformatics and precision medicine.

Keywords

Cite

@article{arxiv.2503.04490,
  title  = {Large Language Models in Bioinformatics: A Survey},
  author = {Zhenyu Wang and Zikang Wang and Jiyue Jiang and Pengan Chen and Xiangyu Shi and Yu Li},
  journal= {arXiv preprint arXiv:2503.04490},
  year   = {2026}
}

Comments

Accepted by ACL 2025

R2 v1 2026-06-28T22:09:18.119Z