Developing quantitative models for understanding complex adaptive processes in biology and medicine


Our research group is focused on developing and applying mathematical and statistical models to explain and predict the behavior of complex biological systems.  Our foundational modeling efforts utilize mathematical analysis, probability and stochastic process theory, and statistical mechanics to describe dynamic biological processes.  Applied work is directed at the development of computational tools for the interpretation of biological phenotypes implicated in health and human disease.  We have applied this approach to understand cancer evolution and immune escape, the recognition capacity of an adaptive immune repertoire, the epithelial-to-mesenchymal transition dynamics, and phenotypic adaptation in stochastic environments with applications to drug resistance and adaptive therapies.

Jason T. George