February 3, 2006
Colloquium Speaker: Frank Doyle
Dr. Frank J. Doyle III is the Associate Director of the Army Institute for Collaborative Biotechnologies. He holds the Duncan and Suzanne Mellichamp Chair in Process Control in the Department of Chemical Engineering at the University of California at Santa Barbara, as well as appointments in the Electrical Engineering Department, and the Biomolecular Science and Engineering Program. He received his B.S.E. from Princeton, C.P.G.S. from Cambridge, and Ph.D. from Caltech, all in Chemical Engineering. Prior to his appointment at UCSB, he has held faculty appointments at Purdue University and the University of Delaware, and held visiting positions at DuPont, Weyerhaeuser, and Stuttgart University. He is the recipient of several research awards (including the NSF National Young Investigator, ONR Young Investigator, and Humboldt Research Fellowship) as well as teaching awards (including the Purdue Potter Award, and the ASEE Ray Fahien Award). He is currently the editor-in-chief of the IEEE Transactions on Control Systems Technology, and holds Associate Editor positions with the Journal of Process Control, the SIAM Journal on Applied Dynamical Systems, and Interface. His research interests are in systems biology, drug delivery for diabetes, and control of particulate processes.
Our research is focused on unraveling the regulatory architectures of complex biological systems. As gene-level architectures become known, the open challenge is to assign predictable behavior to a known structure, the so-called "genotype-to-phenotype" problem. In response to this challenge, the discipline of systems biology has emerged with an integrative perspective towards determining complex systems behavior. A property of particular interest is the robustness of the biophysical network: the ability to maintain some target level of behavior or performance in the presence of uncertainty and/or perturbations. In biological systems, these disturbances can be environmental (heat, pH, etc.) or intrinsic to the organism (changes in kinetic parameters). While preliminary results are available for simple (low-dimensional, deterministic) biological systems, general tools for analyzing these tradeoffs are the subject of active research. In this talk, a number of quantitative tools from systems theory will be presented as enabling methodologies for unraveling robust biological regulatory systems, with an emphasis on sensitivity analysis. Our work on modeling and analysis of the Drosophila circadian rhythm gene network will be detailed, and generalizations will be drawn for the mammalian analog and for more general gene regulatory networks. In addition, a brief overview of the Institute for Collaborative Biotechnologies will be presented, with an emphasis on biologically inspired approaches to materials synthesis and networked control.