Rice University

Events at Rice

Colloquium

Bioengineering

Speaker: Michael Savageau, Ph.D.
Distinguished Professor, Biomedical Engineering
UC Davis

Strategy For Deconstructing Complex Systems By Phenotypes

Tuesday, November 18, 2014
4:00 PM  to 5:00 PM

280  Brown College
Rice University
6100 Main St
Houston, Texas, USA

The announcement of the draft sequence of the human genome revealed the true magnitude of the Grand Challenge involved in relating genotype to phenotype. Although we now have a generic concept of ‘genotype’ provided by the detailed DNA sequence, there is no corresponding generic concept of ‘phenotype’. Without a generic concept of phenotype there can be no rigorous framework for a deep understanding of the complex biochemical systems that link genotype to phenotype. The task of relating the two could be facilitated if these systems could be generically decomposed into a series of tractable subsystems representing the full phenotypic repertoire and if the results of their analysis could be reassembled to provide insight into the original system. I will describe advances in a novel approach that addresses these important challenges. It provides a generic definition of phenotype and automatically identifies the corresponding subsystems. The qualitatively distinct phenotypes of a complex system can then be rigorously defined and counted, their fitness analyzed and compared, their global tolerances measured, and their biological design principles revealed. A few simple applications will be used to illustrate how this approach elucidates the relationship between genotypically determined parameters, environmentally determined variables, and the qualitatively distinct phenotypes of biochemical systems. This approach has provided quantitative understanding for a number of natural systems. The global perspective on the behavioral repertoire also facilitates comparisons of alternative systems and assists in the rational design of synthetic constructs.

Biography of Michael Savageau, Ph.D.:

Distinguished Professor, The University of California Davis, holds degrees from The University of Minnesota (B.S.), The University of Iowa (M.S.), and Stanford University (Ph.D.). He was a postdoctoral fellow at both UCLA and Stanford University prior to joining the faculty at The University of Michigan. Dr. Savageau initiated Michigan’s interdisciplinary training program in Cellular Biotechnology and its interdisciplinary Bioinformatics Program. He also chaired the Department of Microbiology and Immunology from 1992-2002 and was named the Nicolas Rashevsky Distinguished University Professor in 2002. After moving to the University of California Davis in 2003 he chaired the Department of Biomedical Engineering from 2003 to 2005. His honors include Guggenheim Fellow, Fulbright Senior Research Fellow, Michigan Society of Fellows, Foundation for Microbiology Lecturer, American Association for the Advancement of Science Fellow, Institut des Hautes Études Scientifiques Award, Moore Distinguished Scholar at the California Institute of Technology, Member of the National Academies of Science Institute of Medicine, 79th Josiah Willard Gibbs Lecturer for the American Mathematical Society, American Institute for Medical and Biological Engineering Fellow, Stanislaw Ulam Distinguished Scholar Award from the Center for Non-Linear Studies, Los Alamos National Laboratory, Honorary Doctor of Science, Universitat de Lleida, Spain, Fellow, Institute of Electrical and Electronic Engineers, and The Michael A. Savageau Collegiate Professorship in Computational Medicine and Bioinformatics permanently endowed by the University of Michigan. He was Editor-in- Chief of Mathematical Biosciences from 1995 to 2005, and serves on advisory panels for the National Institutes of Health, the National Science Foundation, the Howard Hughes Medical Institute, the Keck Foundation, and the National Academies of Science. He lectures extensively in the US and abroad on his research, which is focused on mathematical methods for the comparative analysis of function, design and evolution of gene circuitry.



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