Advancing Bioinformatics, Translational Bioinformatics and Computational Biology Research (R01 Clinical Trial Optional)

The National Library of Medicine (NLM), a component of the National Institutes of Health (NIH), is offering a funding opportunity titled “Advancing Bioinformatics, Translational Bioinformatics and Computational Biology Research (R01 Clinical Trial Optional).” This initiative reflects NLM’s overarching mission to promote innovation in biomedical informatics and computational biology in order to advance biomedical discovery and improve health outcomes. This Notice of Funding Opportunity (NOFO) invites research proposals aimed at developing cutting-edge tools, methodologies, and approaches that can harness the power of complex and large-scale biomedical datasets. The central focus is on driving transformative advances through the application of technologies such as artificial intelligence (AI), machine learning, and scalable computing platforms to extract and interpret actionable knowledge from biological data. The funding supports research that extends across bioinformatics and computational biology domains—from omics-level analysis to systems biology and data integration studies. Key objectives include the development of functional tools and resources that are generalizable across diseases and biological systems, rather than narrowly tailored to specific conditions. Proposed projects should yield durable, widely applicable tools or methods with strong usability, autonomous update capabilities, and alignment with FAIR (Findable, Accessible, Interoperable, and Reusable) principles. Importantly, tools and methods must be shared in open, well-documented repositories accessible to the broader scientific community, with provisions for long-term maintenance and ethical use of data. Applicants are encouraged to propose interdisciplinary and scalable innovations that go beyond predictive modeling and instead aim to uncover biological mechanisms or pathways. These could range from omics-based studies to research on drug targets, regulatory networks, biomarker discovery, and single-cell informatics. Projects involving methodological advances in AI and ML, network studies at the organismal level, or data harmonization and reuse are also within scope. Applications must provide detailed research plans with defined metrics, clear use cases, evaluation strategies, benchmarking approaches, and plans for dissemination. Experimental validation is permitted only as a minor component; the primary emphasis should remain on computational innovation. Eligibility for this program is broad, encompassing U.S. and foreign entities such as higher education institutions, non-profit and for-profit organizations, government entities at various levels (state, county, local, tribal), and international collaborations, provided they comply with NIH policies. However, foreign subawards or subcontracts involving monetary compensation are prohibited unless submitted under a specific international NOFO. All individuals with the necessary expertise are encouraged to apply as Program Directors or Principal Investigators (PD/PIs), though they must register through required systems such as eRA Commons and Grants.gov. Applications may be submitted beginning April 6, 2026, and follow the NIH Standard Due Dates: June 5, October 5, and February 5 (with renewal/resubmission dates following in July, November, and March, respectively). This cycle recurs annually through February 2029. Projects may request up to $250,000 in direct costs annually for up to four years, with the budget to reflect the scope and needs of the project. There is no mandatory cost-sharing requirement. All applications must be submitted electronically through NIH ASSIST, Grants.gov Workspace, or an institution's S2S system, and adhere strictly to the NIH Application Guide and the instructions in this NOFO. Review of applications will be based on the standard NIH review criteria, with additional emphasis on innovation, scientific rigor, and feasibility. Factors such as generalizability, benchmarking strategies, maintenance plans, and dissemination approaches will be critical to the evaluation. The anticipated award start dates follow the advisory council reviews: April, July, and December each year. Award recipients are expected to disseminate results widely, maintain open-access resources, and comply with NIH data-sharing and cybersecurity standards. Scientific, review, and grants management contacts are provided through NLM’s Extramural Programs Office, ensuring applicants can seek guidance throughout the submission process.

10–15 hours