EAGER: Computationally Predicting and Characterizing the Immune Response to Viral Infectio — NSF Award to University of Minnesota-
Pathogens such as the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) affect different people differently. Whether an individual mounts a strong response or not depends, at least in part, on their genes. Specific genes code for the proteins on the surface of cells that present viral protein fragments to th
| Award title | EAGER: Computationally Predicting and Characterizing the Immune Response to Viral Infectio |
|---|---|
| Award ID | 2036064 |
| Awardee | University of Minnesota-Twin Cities |
| City | MINNEAPOLIS |
| State | MN |
| Amount obligated | $200,000 |
| Principal investigator | Marc Riedel |
| Program | FET-Fndtns of Emerging Tech |
| Start date | 08/01/2020 |
| Abstract | Pathogens such as the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) affect different people differently. Whether an individual mounts a strong response or not depends, at least in part, on their genes. Specific genes code for the proteins on the surface of cells that present viral protein fragments to the immune system. Killer T cells recognize these fragments and kill the infected cells. The immune response to SARS-CoV-2 hinges on whether the viral protein fragments bind into a g |
| Source | NSF Awards |
$799/mo
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