CAREER: Scalable algorithms for regularized and non-linear genetic models of gene expressi — NSF Award to University of California
DNA mutations have a profound effect on how genes work, but it’s still not well understood which mutations affect which genes. Currently, our knowledge is limited due to challenges in analyzing genomics data, such as statistical errors arising from an overrepresentation of study participants from specific groups and si
| Award title | CAREER: Scalable algorithms for regularized and non-linear genetic models of gene expressi |
|---|---|
| Award ID | 2336469 |
| Awardee | University of California-San Diego |
| City | LA JOLLA |
| State | CA |
| Amount obligated | $444,000 |
| Principal investigator | Tiffany Amariuta-Bartell |
| Program | Info Integration & Informatics |
| Start date | 03/01/2024 |
| Abstract | DNA mutations have a profound effect on how genes work, but it’s still not well understood which mutations affect which genes. Currently, our knowledge is limited due to challenges in analyzing genomics data, such as statistical errors arising from an overrepresentation of study participants from specific groups and simplistic statistical models that do not sufficiently capture the data. This project overcomes these challenges across three main scientific goals, in which innovative statistical m |
| Source | NSF Awards |
$799/mo
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