Large Language Models in Bioinformatics: A Survey
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arXiv
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| Hauptverfasser: | , , , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| _version_ | 1866917300864548864 |
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| author | Wang, Zhenyu Wang, Zikang Jiang, Jiyue Chen, Pengan Shi, Xiangyu Li, Yu |
| author_facet | Wang, Zhenyu Wang, Zikang Jiang, Jiyue Chen, Pengan Shi, Xiangyu Li, Yu |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_04490 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Large Language Models in Bioinformatics: A Survey Wang, Zhenyu Wang, Zikang Jiang, Jiyue Chen, Pengan Shi, Xiangyu Li, Yu Computation and Language Genomics 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. |
| title | Large Language Models in Bioinformatics: A Survey |
| topic | Computation and Language Genomics |
| url | https://arxiv.org/abs/2503.04490 |