Advancing Bioinformatics, Translational Bioinformatics and Computational Biology Research (R01 Clinical Trial Optional)
- Deadline
- Mar 5, 2029
- Posted
- Feb 11, 2026
- Award amount
- Up to $250,000
- Focus areas
- Health
Who can apply
Refer to Section III. Eligibility Information in the NOFO for additional information on eligibility.Foreign Organizations/International CollaborationsNon-domestic (non-U.S.) Entities (Foreign Organizations) are eligible to apply.Non-domestic (non-U.S.) components of U.S. Organizations are eligible to apply.Foreign components, as defined in the NIH Grants Policy Statement, are allowed.NIH will no longer issue awards (i.e., new, renewal, or non-competing continuation) to domestic or foreign entities that involve foreign subawards/subcontracts. All NIH-funded research involving foreign subawards/subcontracts must be submitted in response to a NOFO that is specifically designated for funded international collaborations. This new requirement was effective, May 1, 2025.Applications involving foreign subawards/subcontracts submitted in response to this NOFO will be deemed noncompliant and will not be considered for funding. This policy applies to all monetary international collaborations resulting in foreign subawards/subcontracts, however, it does not preclude unfunded international collaborations or foreign components, funding for foreign consultants, or procurement of unique equipment or supplies from foreign vendors.
About this grant
The National Library of Medicine (NLM) seeks applications for research projects that drive groundbreaking innovation and advanced development in the fields of bioinformatics, translational bioinformatics, and computational biology. The primary goal of this initiative is to support the creation and implementation of cutting-edge methods, tools, and approaches that can transform the landscape of biomedical data science. This NOFO aims to address the growing need to leverage transformative technologies — such as artificial intelligence (AI), machine learning, and large-scale computational platforms — to extract actionable knowledge from vast, diverse, and complex biological datasets. By enabling more effective interpretation and integration of multi-dimensional biological and biomedical data, this research will ultimately contribute to improving individual and population health outcomes.
Source: public records via Grants.gov. UseGrants is an independent aggregator, not affiliated with any funding agency. Always confirm details on the official listing before applying.