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Listening to the noise: stochastic gene expression in molecular systems biology

Modeling biochemical reaction networks is key to understanding life at the most basic level. One of the challenges to the analysis and synthesis of genetic networks is that the cellular environment in which these circuits function is abuzz with 'noise' originating from the inherent random motion of reacting molecules in the living cell. In this noisy environment, clonal cell populations show cell-to-cell variability that can manifest significant phenotypic differences. In this talk, we motivate the need for stochastic models and outline the key tools for the modeling and analysis of stochasticity inside living cells. We then show that noise induced random fluctuations convey valuable information about the underlying genetic network. Far from being a nuisance, the ever-present cellular noise acts as a rich source of excitation that carries a gene network's distinctive fingerprint and encodes a wealth of information about that network. The analysis of these random fluctuations enables the identification of network parameters, including those that may otherwise be difficult to measure. This establishes a potentially powerful approach for the identification of gene networks and offers a new window into their dynamic character.
Type of Seminar:
Public Seminar
Prof. Mustafa Khammash
Director Center for Control, Dynamical-systems, and Computation (CCDC), University of California at Santa Barbara
Nov 04, 2009   17:15 /

ETZ E6, Gloriastrasse 35, Zurich
Contact Person:

John Lygeros
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Biographical Sketch:
Mustafa Khammash is the Director of the Center for Control, Dynamical systems, and Computations (CCDC) and a Professor of Mechanical Engineering at the University of California at Santa Barbara (UCSB). He received his B.S. degree from Texas A&M University in 1986 and his Ph.D. from Rice University in 1990, both in electrical engineering. Before joining UCSB in 2002 he was with the Electrical Engineering Department at Iowa State University. Khammash’s current research interest uses control theory for the quantitative analysis of biological networks with the goal of reverse engineering their complexity. He is also developing computational methods for the analysis of stochastic dynamics and their applications in the area of Systems Biology. Khammash is a Fellow of the IEEE and the recipient of the National Science Foundation Young Investigator Award, the Japan Society for the Promotion of Science (JSPS) Fellowship, and the ISU Foundation Early Achievement in Research and Scholarship Award.