Large Language Models in Bioinformatics: A Survey

Zhenyu Wang, Zikang Wang, Jiyue Jiang, Pengan Chen, Xiangyu Shi +1 more
3/6/2025
cs.CLq-bio.GN

No official code found. Best implementation: jiangjyjy/Bioinformatics_LLM_Survey (3 stars, last commit 2025-08-10).

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.

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[ACL 2025] Large Language Models in Bioinformatics: A Survey

30Aug 10, 20251 years ago

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Cite this paper

@article{wang2025large,
  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},
  year   = {2025},
  eprint = {2503.04490},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2503.04490v2}
}

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