{
  "abstract": "Large language models (LLMs) are a class of artificial intelligence models based on deep learning, which have great performance in various tasks, especially in natural language processing (NLP). Large language models typically consist of artificial neural networks with numerous parameters, trained on large amounts of unlabeled input using self-supervised or semi-supervised learning. However, their potential for solving bioinformatics problems may even exceed their proficiency in modeling human language. In this review, we will provide a comprehensive overview of the essential components of large language models (LLMs) in bioinformatics, spanning genomics, transcriptomics, proteomics, drug discovery, and single-cell analysis. Key aspects covered include tokenization methods for diverse data types, the architecture of transformer models, the core attention mechanism, and the pre-training processes underlying these models. Additionally, we will introduce currently available foundation models and highlight their downstream applications across various bioinformatics domains. Finally, drawing from our experience, we will offer practical guidance for both LLM users and developers, emphasizing strategies to optimize their use and foster further innovation in the field.",
  "abstract_shown": true,
  "affiliations": [
    "Center for Computational Systems Medicine, McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston , 7000 Fannin St, Houston, Houston, TX 77030 ,",
    "Center for Computational Systems Medicine, McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, Texas, 77030, USA",
    "Department of Cell Biology and Genetics, School of Basic Medical Sciences, Xi’an Jiaotong University Health Science Center , No. 28 Xianning West Road, Xian City, Shaanxi Province, 710049, P.R",
    "School of Life Sciences, Zhengzhou University, Zhengzhou, Henan 450001, China",
    "School of Computing and Artificial Intelligence, Southwest Jiaotong University , No. 999, Xi'an Road, Pidu District, Chengdu, Sichuan, 611756, P.R",
    "School of Computing and Artificial Intelligence, Southwest Jiaotong University, Chengdu, Sichuan 611756, China",
    "The Center of Gerontology and Geriatrics, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China",
    "West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China",
    "West China Biomedical Big Data Center, West China Hospital, Sichuan University , No. 17, Section 3, South Renmin Road, Chengdu, Sichuan, 610041, P.R",
    "McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA",
    "School of Dentistry, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA",
    "McGovern Medical School, The University of Texas Health Science Center at Houston , 6431 Fannin St, Houston, Houston, TX 77030 ,",
    "School of Dentistry, The University of Texas Health Science Center at Houston , 7500 Cambridge St, Houston, TX 77030 ,"
  ],
  "article_type": "review",
  "arxiv": null,
  "author_total": 7,
  "authors": [
    {
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        0,
        1
      ],
      "name": "Jiajia Liu",
      "orcid": "0000-0002-0038-9592"
    },
    {
      "affs": [
        2,
        3
      ],
      "name": "Mengyuan Yang",
      "orcid": "0009-0005-2342-0993"
    },
    {
      "affs": [
        4,
        5
      ],
      "name": "Yankai Yu",
      "orcid": "0009-0004-7441-5804"
    },
    {
      "affs": [
        0,
        6,
        7
      ],
      "name": "Haixia Xu",
      "orcid": "0009-0009-0300-5900"
    },
    {
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        0,
        7
      ],
      "name": "Tiangang Wang"
    },
    {
      "affs": [
        8,
        1,
        9,
        10
      ],
      "name": "Kang Li",
      "orcid": "0000-0002-8136-9816"
    },
    {
      "affs": [
        0,
        11,
        12
      ],
      "name": "Xiaobo Zhou",
      "orcid": "0000-0002-5584-5807"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/ah87zmq7tpk8n.bib",
  "cited_by": 61,
  "doi": "10.1093/bib/bbag367",
  "fulltext_url": null,
  "id": "ah87zmq7tpk8n",
  "issns": [
    "1467-5463",
    "1477-4054"
  ],
  "landing_url": "https://doi.org/10.1093/bib/bbag367",
  "language": "en",
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "1312|Machine Learning in Bioinformatics"
    ]
  ],
  "openalex": "W4390783938",
  "pdf_url": null,
  "pmcid": "PMC10802675",
  "pmid": "38259343",
  "published": "2026-07-01",
  "publisher": "Oxford University Press",
  "ris": "https://research.draconitic.com/paper/ah87zmq7tpk8n.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T13:26:46Z",
      "native_id": "W4390783938",
      "source": "openalex",
      "url": "https://doi.org/10.1093/bib/bbag367"
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  "subjects": [
    {
      "field": "biochemistry",
      "origin": "openalex:1312|Machine Learning in Bioinformatics",
      "subfield": "molecular-biology"
    }
  ],
  "title": "Advancing bioinformatics with language models: components, applications, and perspectives",
  "title_text": "Advancing bioinformatics with language models: components, applications, and perspectives",
  "type": "peer-reviewed",
  "updated_at": "2026-11-09T13:21:05Z",
  "url": "https://research.draconitic.com/paper/ah87zmq7tpk8n",
  "venue": "Briefings in Bioinformatics",
  "versions": []
}