CAREER: Decoding gene regulatory mechanisms with AI and population-scale multi-omics — NSF Award to University of North Carolina a
Modern biology has entered an era in which the central challenge is not the lack of data, but how to organize large and complex datasets into knowledge that scientists can understand and test. Artificial Intelligence has greatly improved the ability to find patterns in biological data, but many models still struggle to
| Award title | CAREER: Decoding gene regulatory mechanisms with AI and population-scale multi-omics |
|---|---|
| Award ID | 2543774 |
| Awardee | University of North Carolina at Chapel Hill |
| City | CHAPEL HILL |
| State | NC |
| Amount obligated | $598,807 |
| Principal investigator | Elizabeth Brunk |
| Program | Tools, Inform & Func Geno |
| Start date | 06/01/2026 |
| Abstract | Modern biology has entered an era in which the central challenge is not the lack of data, but how to organize large and complex datasets into knowledge that scientists can understand and test. Artificial Intelligence has greatly improved the ability to find patterns in biological data, but many models still struggle to explain the biological mechanisms behind those patterns. This project addresses that challenge by developing new ways to use Artificial Intelligence to understand gene regulation, |
| Source | NSF Awards |
$799/mo
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