Data Coordinating Center for the Aging and Alzheimer’s Disease Mouse Brain Atlas (AD-MBA) (U24 Clinical Trial Not Allowed)
National Institute on Aging (NIA) · NIH Institute/Center · RFA-AG-27-010
Source: Grants.gov · View original posting ↗
- AwardWhat a single award can be worth — the funder's published per-award amount or floor–ceiling range.
- $2.5M total
- DeadlineFinal application due date.
- Nov 10, 2026
- 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, …).
- U24
- DurationMaximum project period for a single award.
- —
- Expected awardsHow many awards the funder anticipates making under this opportunity.
- 1
- Funding cycleHow often the program accepts applications (annual, multiple cycles per year, rolling, or one-time).
- One-time
- Open dateWhen applications open (or opened).
- Sep 1, 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.
- Not allowed
Research areas
Auto-classified from the title and description (keyword-based) — may be imperfect.
Description
This Notice of Funding Opportunity (NOFO) invites applications proposing a Data Coordinating Center that integrates and disseminates multiscale mouse brain datasets for the aging and Alzheimer's disease (AD) research community. The Data Coordinating Center will establish the Aging and AD Mouse Brain Atlas (AD-MBA), which will serve as a central, unified research resource for multi-omic and connectomic mouse brain datasets emerging from the NIA AD Multimodal Atlas Projects (AD-MAPs). The Data Coordinating Center will (1) leverage the NIA-supported AD Knowledge Portal data infrastructure to facilitate hosting, deposition, and dissemination of multimodal datasets generated by the AD-MAPs program, (2) facilitate collaborative analyses among the data-contributing teams, (3) develop/optimize and incorporate tools for multiscale integration of multi-omics and connectomics datasets, and (4) create a broadly accessible web-based interface for the visualization and dissemination of integrated multiscale data.