Friday, November 22, 2024
11/22/2024
PROJECT SUMMARY/ABSTRACT Despite recent experimental advances in high-dimensional time-course data generation and accompanying inferential statistical approaches, we still lack the ability to reliably estimate the time-dynamical adaptation mechanisms that biological systems utilize to navigate varying environments. The major obstacle preventing a mechanistic understanding of dynamic adaptation is an absence of hybrid theory- and data-driven models that integrate biological mechanisms of adaptation with their effects on state transitions and associated fitness in a variable environment. By leveraging my prior expertise in modeling stochastic biological processes and building upon our recent mathematical characterization of optimized adaptation strategies, this research project will develop a comprehensive computational framework to address this need. In the next five to ten years, we will address three main research goals: 1) design a mathematical framework for tracking the effects of variable, time- dependent adaptation, 2) validate computational models accounting for dynamic adaptability using time-course gene expression and sequencing data, and; 3) apply, in close experimental and clinical collaboration, the modeling framework to understand disease-specific adaptability through antigen signatures that evolve in the presence of an adaptive T cell immune repertoire. Since dynamic adaptation is fundamental to many biological processes with therapeutic implications for treatment resistance, this modeling framework will be useful for predicting the time-dependent effects of prior environmental histories on the phenotypic outcome of adaptive systems. Such predictions will also enable additional in silico evaluation of the effects of intervention on disease outcome. The proposed research will improve our understanding of the general principals governing dynamic adaptation in biological systems and provide a more comprehensive characterization of the role of antigenic adaptability in the setting of a time-varying immune environment.
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