Advancing Bioinformatics, Translational Bioinformatics and Computational Biology Research (R01 Clinical Trial Optional)
National Institutes of Health (NIH) · NIH Institute/Center · PAR-26-040
Source: Grants.gov · View original posting ↗
- AwardWhat a single award can be worth — the funder's published per-award amount or floor–ceiling range.
- Up to $250K
- DeadlineFinal application due date.
- Mar 5, 2029
- Letter of intentDue date for the letter of intent (a short pre-application some funders require or request before the full proposal).
- —
- MechanismNIH activity code — the grant type (R01 research project, R21 exploratory, K series career development, F series fellowship, …).
- R01
- DurationMaximum project period for a single award.
- —
- Expected awardsHow many awards the funder anticipates making under this opportunity.
- 10
- Funding cycleHow often the program accepts applications (annual, multiple cycles per year, rolling, or one-time).
- Standard NIH dates
- Open dateWhen applications open (or opened).
- Feb 11, 2026
- Total fundingThe overall pool the funder expects to commit across ALL awards under this opportunity — not what one project receives.
- $2.5M total
- Clinical trialWhether proposed projects must, may, or must not include a clinical trial.
- Optional / allowed
Funding context
Based on FY2024 NIH (all institutes) R01 applications (5,385 of 33,139 applications awarded).
Institute-specific data wasn’t available — showing the NIH-wide rate for this mechanism.
Payline: NIH discontinued percentile paylines for 2026 under its Unified Funding Strategy ↗ — scores are now weighed in context rather than against a fixed cutoff.
NIH-wide R01, all institutes.
Aggregate historical data by institute, mechanism, and fiscal year — context for planning, not a prediction for this opportunity. Source ↗
Research areas
Auto-classified from the title and description (keyword-based) — may be imperfect.
Description
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.
Data notes: administering NIH institute could not be identified from the opportunity number.