This Project Grant award from the National Science Foundation (NSF) under the Mathematical and Physical Sciences (CFDA 47.049) Federal Grant Program provides $599,999 to Duke University for a project titled "Challenges in Stochastic Modeling and Computation for Sequential Vaccine Design." The project aims to address technical challenges in computational modeling of the stochastic immune system in order to improve methods for estimating the probability of inducing broadly protective antibodies through vaccine regimens. The key research objectives are to: (1) compute the probability of inducing a mature antibody sequence from its unmutated ancestor, (2) cluster sequences into clones with a common evolutionary ancestor, and (3) reconstruct the evolutionary history of antibody maturation within B cell clones. The project will advance these capabilities by incorporating sequence context-dependence into stochastic evolutionary models of antibody maturation and developing new efficient computational algorithms. This 3-year award, effective June 1, 2024, supports Duke University's research to help design more effective vaccine strategies by better understanding the stochastic processes underlying antibody generation.
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