Harnessing Large Cohorts and AI to Bridge Genomic Discovery and Clinical Practice
Large-scale population cohorts have become a cornerstone of modern biomedical research, enabling systematic discovery of disease mechanisms, refining risk stratification, and advancing precision medicine into reality.By integrating multi-omics and deep phenotypic data, these resources provide a powerful foundation for uncovering biological drivers of health and disease, guiding prevention strategies, and improving population health outcomes.In the current era marked by the rapid emergence of artificial intelligence (AI), data from large-scale population cohorts are becoming increasingly indispensable.Despite remarkable progress, population-scale studies still face fundamental challenges, including limited diversity, inequitable representation, incomplete coverage of certain omics layers, and persistent barriers to
Authors
- Minxian Wang (ORCID: https://orcid.org/0000-0002-3753-508X)
- Bitao Zhong (ORCID: https://orcid.org/0000-0003-3537-6107)
- Xiaoxi Jing (ORCID: https://orcid.org/0000-0003-0642-8641)
- Yajie Zhao (ORCID: https://orcid.org/0000-0002-2747-0219)
- Aniruddh P. Patel (ORCID: https://orcid.org/0000-0001-7871-9638)
- Shaoqi Wang (ORCID: https://orcid.org/0009-0009-8355-6103)
Institutions
- Broad Institute (US)
- Chinese Academy of Sciences (CN)
- Beijing Institute of Genomics (CN)
- Massachusetts General Hospital (US)
- Center for Genomic Science (IT)
- Shanghai Center For Bioinformation Technology (CN)
- University of Chinese Academy of Sciences (CN)
Publication Details
- Journal
- Genomics Proteomics & Bioinformatics
- Published
- 2025-10-01
- DOI
- https://doi.org/10.1093/gpbjnl/qzaf104
- Primary Topic
- Genomics and Rare Diseases
- Type
- article
- Field-Weighted Citation Impact
- 0.00