Evolution@Vanderbilt

Research Interests: The overall goal of our cancer systems biology approach is to build quantitative hypotheses that translate experimental observations or datasets into computer simulations, based on mathematical modeling techniques including ordinary or partial differential equations, cellular automata, neural networks, immersed boundary method, game theory, Boolean networks. To test these hypotheses, we populate these models with datasets from in vitro or animal experiments, or from clinical material. We then design and perform experiments to validate these predictions, and the outcome of the experimentation is used to evaluate the realism of computer simulations and possibly modify their underlying mathematics. Our group is comprised of an interdisciplinary collection of scientists, including cell and molecular biologists, mathematicians, engineers, bioengineers, bioinformaticians and computational biologists. Our team science thrives on continued personal exchanges among these diverse scientists, looking at cancer research problems through the lenses of different disciplines.

Keywords: Cancer systems biology, drug synergy, epigenetic landscape, phenotypic heterogeneity and state transitions, clonal evolution, anti-cancer therapy