{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Mardinoglu A"],"funding":["National Research Foundation of Korea (NRF)","Knut och Alice Wallenbergs Stiftelse","National Research Foundation of Korea","Knut och Alice Wallenbergs Stiftelse (Knut and Alice Wallenberg Foundation)"],"pagination":["1147-1165"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC12405541"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["21(9)"],"pubmed_abstract":["Generating longitudinal and multi-layered big biological data is crucial for effectively implementing artificial intelligence (AI) and systems biology approaches in characterising whole-body biological functions in health and complex disease states. Big biological data consists of multi-omics, clinical, wearable device, and imaging data, and information on diet, drugs, toxins, and other environmental factors. Given the significant advancements in omics technologies, human metabologenomics, and computational capabilities, several multi-omics studies are underway. Here, we first review the recent application of AI and systems biology in integrating and interpreting multi-omics data, highlighting their contributions to the creation of digital twins and the discovery of novel biomarkers and dr"],"journal":["Molecular systems biology"],"pubmed_title":["Longitudinal big biological data in the AI era."],"pmcid":["PMC12405541"],"funding_grant_id":["NRF-2023-R1A2C3003438","72254"],"pubmed_authors":["Turkez H","Uhlen M","Srinivasulu VP","Hood L","Mardinoglu A","Palsson BO","Shong M","Nielsen J"],"additional_accession":[]},"is_claimable":false,"name":"Longitudinal big biological data in the AI era.","description":"Generating longitudinal and multi-layered big biological data is crucial for effectively implementing artificial intelligence (AI) and systems biology approaches in characterising whole-body biological functions in health and complex disease states. Big biological data consists of multi-omics, clinical, wearable device, and imaging data, and information on diet, drugs, toxins, and other environmental factors. Given the significant advancements in omics technologies, human metabologenomics, and computational capabilities, several multi-omics studies are underway. Here, we first review the recent application of AI and systems biology in integrating and interpreting multi-omics data, highlighting their contributions to the creation of digital twins and the discovery of novel biomarkers and dr","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025 Sep","modification":"2026-05-29T21:16:23.107Z","creation":"2026-04-08T05:57:22.903Z"},"accession":"S-EPMC12405541","cross_references":{"pubmed":["40764831"],"doi":["10.1038/s44320-025-00134-0"]}}