{
  "abstract": "Microbiome systems encompass diverse ecological niches and host associations, with their scale and complexity challenging traditional analytical frameworks. Advances in artificial intelligence are transforming microbiome research by enabling improved integrative analyses of microbial genomes, community structure, and functional potential. In this Review, we outline how these developments create opportunities for microbiome research to move beyond descriptive analyses towards predictive modelling and hypothesis generation, including emerging insights into microbial function, host-microbe interactions, and ecosystem-level organisation. As the field grapples with challenges in model interpretability, generalisability, and causal inference, emerging strategies, such as multiomics and multicohort integration, provide promising avenues to deepen biological understanding. Addressing ethical considerations, including data privacy, algorithmic bias, and equitable access, will be crucial for translating artificial intelligence-driven microbiome discoveries into robust and inclusive clinical applications.",
  "abstract_shown": true,
  "affiliations": [
    "MOE Key Laboratory of Geriatric Diseases and Immunology, The Second Affiliated Hospital of Soochow University, Soochow University, Suzhou, China",
    "Institute of Clinical Pharmacology, Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing, China",
    "Department of Pediatrics, Key Laboratory of Birth Defects and Related Diseases of Women and Children, West China Second University Hospital, Sichuan University, Chengdu, China",
    "National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, School of Medicine, Sun Yat-sen University, Shenzhen, China; Shenzhen Key Laboratory for Systems Medicine in Inflammatory Diseases, Sun Yat-sen University, Shenzhen, China; Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China",
    "Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA",
    "Teagasc Food Research Centre, Moorepark, Fermoy, Ireland; APC Microbiome Ireland, University College Cork, Cork, Ireland",
    "State Key Laboratory of Microbial Metabolism, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China",
    "Zhejiang Provincial Key Laboratory of Pancreatic Disease, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China",
    "Department of Urology, Zhongshan Hospital, Fudan University, Shanghai, China; Department of Kidney Transplantation, Zhongshan Hospital, Fudan University, Shanghai, China; Shanghai Key Laboratory of Organ Transplantation, Shanghai, China; Shanghai Medical College, Fudan University, Shanghai, China",
    "Department of Urology, Zhongshan Hospital, Fudan University, Shanghai, China",
    "APC Microbiome Ireland, University College Cork, Cork, Ireland",
    "State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China. Electronic address: clevelandhuangyuan@163.com"
  ],
  "article_type": "review",
  "arxiv": null,
  "author_total": 15,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Wanqian Yu"
    },
    {
      "affs": [
        1
      ],
      "name": "Hua Qu"
    },
    {
      "affs": [
        2
      ],
      "name": "Shaopu Wang",
      "orcid": "0000-0003-2803-5814"
    },
    {
      "affs": [
        3
      ],
      "name": "Mǎng Shī",
      "orcid": "0000-0002-6154-4437"
    },
    {
      "affs": [
        4
      ],
      "name": "Yingzhou Lu",
      "orcid": "0009-0008-7774-6018"
    },
    {
      "affs": [
        0
      ],
      "name": "Shuting Xia"
    },
    {
      "affs": [
        5
      ],
      "name": "Catherine Stanton",
      "orcid": "0000-0002-6724-7011"
    },
    {
      "affs": [
        6
      ],
      "name": "Chenhong Zhang"
    },
    {
      "affs": [
        7
      ],
      "name": "Yuhao Wang",
      "orcid": "0000-0002-4539-3720"
    },
    {
      "affs": [
        8
      ],
      "name": "Tongyu Zhu",
      "orcid": "0000-0002-6197-0698"
    },
    {
      "affs": [
        9
      ],
      "name": "Dong Zhu"
    },
    {
      "name": "Xin Zhou",
      "orcid": "0000-0001-8089-4507"
    },
    {
      "affs": [
        10
      ],
      "name": "R Paul Ross",
      "orcid": "0000-0003-4876-8839"
    },
    {
      "name": "Zhemin Zhou"
    },
    {
      "affs": [
        11
      ],
      "name": "Yuan Huang",
      "orcid": "0000-0002-1420-8932"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/9jy40ewmpe1ap.bib",
  "cited_by": 6,
  "doi": "10.1016/j.lanmic.2026.101428",
  "fulltext_url": null,
  "id": "9jy40ewmpe1ap",
  "issns": [
    "2666-5247"
  ],
  "landing_url": "https://doi.org/10.1016/j.lanmic.2026.101428",
  "language": "en",
  "licence": "CC-BY-NC-ND",
  "licence_label": "CC BY-NC-ND",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by-nc-nd/4.0/",
  "metadata_licence": null,
  "native_subjects": [
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      "1312|Gut microbiota and health"
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  "openalex": "W7162815856",
  "pdf_url": null,
  "pmcid": null,
  "pmid": "42208955",
  "published": "2026-05-29",
  "publisher": "Elsevier BV",
  "ris": "https://research.draconitic.com/paper/9jy40ewmpe1ap.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T13:26:48Z",
      "native_id": "W7162815856",
      "source": "openalex",
      "url": "https://doi.org/10.1016/j.lanmic.2026.101428"
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  "subjects": [
    {
      "field": "biochemistry",
      "origin": "openalex:1312|Gut microbiota and health",
      "subfield": "molecular-biology"
    }
  ],
  "title": "From microbiomes to predictive ecosystems: challenges and opportunities in artificial intelligence-based approaches",
  "title_text": "From microbiomes to predictive ecosystems: challenges and opportunities in artificial intelligence-based approaches",
  "type": "peer-reviewed",
  "updated_at": "2026-11-01T13:20:13Z",
  "url": "https://research.draconitic.com/paper/9jy40ewmpe1ap",
  "venue": "The Lancet Microbe",
  "versions": []
}