Genetic networks: Dynamics, inference, analysis and evolution

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Genetic networks can be viewed as the control systems of living cells. Inferring regulatory relationships between genes, which implement this control system, is one of the fundamental problems in molecular biology. Advances in technologies for measuring the abundances of biomolecules, and interactions between them, are providing revolutionary new data for solving this problem, yielding detailed pictures of individual genes as well as cell-wide snapshots of gene activity and interactions. However, the quantity of the data, and uncertainties in it, necessitate new computational approaches for extracting meaningful information. The overall goal of my research is to advance both the theory and practice of the analysis of high-throughput molecular biology data, ultimately providing mathematical and computational tools that are efficient and robust enough to become part of the standard analysis toolkit of molecular biologists. My efforts will focus primarily in three areas: (1) Developing theory and algorithms for inferring regulatory relationships between genes, particularly differential equation models. (2) Applying modeling methods to important biological systems. (3) Developing tools for the functional interpretation and genetic networks.