The Evolving Cyberinfrastructure at the National Institutes of Health to Support Data and AI in Biomedical Research
Technological advancements have made biomedicine rich in data. With the generation of enormous volumes of biomedical and clinical data, it has become imperative to support biomedical computing investigators to utilize this wealth of biologically meaningful information. Moreover, advancements in Artificial Intelligence (AI) techniques, in conjunction with improved capabilities in implementing large-scale data processing pipelines, have led to the development of robust computational techniques and algorithms to solve complex biological problems. However, there are many challenges associated with providing researchers with secure systems for accessing biomedical data and computational resources that must be addressed. Establishing and maintaining an impactful data and AI ecosystem to support efforts in advancing biomedical research requires effective, scalable, and standardized information technology solutions, funding programs, and technical guidance that facilitate researchers in utilizing the state-of-the-art. The U.S. National Institutes of Health (NIH) has established novel initiatives to implement a cyberinfrastructure that democratizes secure access to large biomedical datasets and cloud-based computing resources, equipping biocomputing scientists to pursue pioneering research. This workshop will highlight the major issues restraining researchers' access to biomedical datasets and computing infrastructures and will cover the key components of the NIH's cyberinfrastructure aimed at advancing data science and AI research for biomedical applications.
Authors
- Ojas A. Ramwala (ORCID: https://orcid.org/0000-0002-8934-8390)
- Nick Weber
- Sean D. Mooney (ORCID: https://orcid.org/0000-0003-2654-0833)
Institutions
- National Institutes of Health (US)
- University of Washington Medical Center (US)
- Center for Information Technology (US)
Publication Details
- Published
- 2025-12-01
- DOI
- https://doi.org/10.1142/9789819824755_0064
- Primary Topic
- Scientific Computing and Data Management
- Type
- article
- Field-Weighted Citation Impact
- 0.00