CAREER: Learning stochastic spatiotemporal dynamics in single-molecule genetics — NSF Award to University of California-Irvine (CA
The ability to measure which genes are expressed in cells has revolutionized our understanding of biological systems. Discoveries range from pinpointing what makes different cell types unique (e.g., a skin vs. brain cell) to how diseases emerge from genetic mutations. This gene expression data is now a ubiquitously use
| Award title | CAREER: Learning stochastic spatiotemporal dynamics in single-molecule genetics |
|---|---|
| Award ID | 2339241 |
| Awardee | University of California-Irvine |
| City | IRVINE |
| State | CA |
| Amount obligated | $239,517 |
| Principal investigator | Christopher Miles |
| Program | Cellular Dynamics and Function, STATISTICS, MATHEMATICAL BIOLOGY |
| Start date | 07/01/2024 |
| Abstract | The ability to measure which genes are expressed in cells has revolutionized our understanding of biological systems. Discoveries range from pinpointing what makes different cell types unique (e.g., a skin vs. brain cell) to how diseases emerge from genetic mutations. This gene expression data is now a ubiquitously used tool in every cell biologist’s toolbox. However, the mathematical theories for reliably extracting insight from this data have lagged behind the amazing progress of the technique |
| Source | NSF Awards |
$799/mo
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