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Computational tools are playing a rapidly expanding role in biology, both for engineering design and in exploratory science. The main reason is that the dramatic improvements in the measurement and mathematical modeling of basic biochemical and biological processes is making it possible to synthesize large and analytically...
Computational tools are playing a rapidly expanding role in biology, both for engineering design and in exploratory science. The main reason is that the dramatic improvements in the measurement and mathematical modeling of basic biochemical and biological processes is making it possible to synthesize large and analytically intractable models of very complicated phenomenon. Many of these generated models are too complicated to be treated with "black-box" numerical algorithms. Instead, aspects of the biological problems must be exploited, or different formulations investigated, to develop computational procedures that are efficient enough to provide timely feedback to a designer or researcher. In this talk, we describe three cases of the development of computational tools for specific biological applications: electrostatic-based ligand design (drug design), design of micromachined devices for biological applications (biomems), and the analysis of collective behavior in cells based on biochemical network models. In each of these cases we will describe at least as many challenges as solved problems, and then we will conjecture about how to train the next generation of researchers who will continue in this work.
This talk will describe work done by Professor White and Shihhsien Kuo, Jay Bardhan, Michael Altman, Bruce Tidor, Carlos Coelho, Bree Aldridge, JungHoon Lee, and Doug Lauffenberger)