Advancing Bioinformatics, Translational Bioinformatics and Computational Biology Research (R01 Clinical Trial Optional)
National Institutes of Health
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- Posted
- Oct 23, 2025
- Amount
- $250,000
- Closes
- Mar 5, 2029 (in 869 days)
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Classification and identifiers
- Solicitation number
- PAR-26-040
- Assistance listing (CFDA)
- 93.879
Amount
$250,000
Who can apply
Local government agencies, Private colleges and universities, and State government agencies can all apply here. Check the eligibility details below to see if your organization fits.
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 for...
About this opportunity
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,...