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Date: Wednesday, September 23, 2015 (NOTE: Day and date)
Speaker: Dr. Michelle Girvan, Dept. of Physics, University of Maryland
Topic: Elucidating the Role of Network Structure in Gene Regulation: Connecting Models and Data
Time and Location: 1:00 PM, with Q&A to follow; in a 1st floor conference room at the American Center for Physics (www.acp.org), 1 Physics Ellipse, College Park, MD - off River Rd., between Kenilworth Ave. and Paint Branch Parkway.
Abstract: The complex process of genetic control relies upon an elaborate network of interactions between genes. Our goal is to combine simple mathematical models with empirical data to understand the role of network structure in gene regulation. Our modeling efforts focus primarily on Boolean systems, which have received extensive attention as useful model for genetic control. An important aspect of Boolean network models is the stability of their dynamics in response to small perturbations. Previous approaches to studying stability have generally assumed uncorrelated random network structure, even though real gene networks typically have nontrivial topology significantly different from the random network paradigm. To address such situations, we present a general method for determining the stability of large gene networks, given some specified network topology. Additionally, we generalize our framework to handle a variety of more biologically realistic update rules, including non-synchronous update and non-Boolean models, in which there are more than two possible gene states. We discuss the application of our modeling approach to experimentally inferred gene networks, and explore the role of dynamical instability in both the evolution of gene networks and the occurrence of some cancers.
Biography: Michelle Girvan is an Associate Professor in the Department of Physics and the Institute for Physical Science and Technology at the University of Maryland. Her research interests focus on the theory and applications of complex networks. In terms of theory, she has worked extensively on defining and identifying modularity in networks. She currently works on applications of network theory to gene regulation and the spread of ideas. Girvan received her Ph.D. in physics from Cornell University and received undergraduate degrees in physics and math at MIT. Before joining the faculty at the University of Maryland, she was a postdoctoral fellow at the Santa Fe Institute, where she currently serves as a member of the external faculty.