NIDCR Research Grants for Analyses of Existing Genomics Data (R01) (Clinical Trial Not Allowed)
Support for research projects analyzing existing genomics data related to human dental, oral, or craniofacial biology and diseases, using statistical and computational methods to address key research questions.
Funder: National Institutes of Health
Due Dates: June 5, 2025 (New) | July 5, 2025 (Renewal/Resubmission/Revision) | September 7, 2025 (AIDS) | October 5, 2025 (New) | November 5, 2025 (Renewal/Resubmission/Revision) | January 7, 2026 (AIDS) | February 5, 2026 (New) | March 5, 2026 (Renewal/Resubmission/Revision) | May 7, 2026 (AIDS)
Funding Amounts: No budget cap; budgets must reflect actual needs. Project period up to 3 years.
Summary: Supports research analyzing existing genomics data to address questions in human dental, oral, or craniofacial biology and disease using computational/statistical methods.
Key Information: Clinical trials are not allowed. Experimental or in silico validation of results is required. Data sharing is strongly recommended.
Description
This opportunity, offered by the National Institute of Dental and Craniofacial Research (NIDCR) at NIH, supports meritorious research projects that address questions relevant to human dental, oral, or craniofacial (DOC) biology, diseases, and conditions. Projects must analyze existing and publicly available genomic data—optionally integrating other complementary data types—using statistical and computational approaches. Both existing and novel analytic methods (including AI/ML/DL) are encouraged.
A key requirement is that each project must include experimental or in silico work to validate the results of the proposed analysis or to validate a newly developed analytic method. Projects that address oral health disparities or investigate human biological pathways to inform intervention targets or variant pathogenicity are especially encouraged.
All data used should be publicly shared, at least in part, before, during, or after the project period. Projects that do not use any publicly shared data or do not include genomic data analysis are not recommended.
