Colloquium: David Soloveichik Fellow UCSF Center for Systems and Synthetic Biology Title: What Can Chemical Reaction Networks Compute? Date: Friday, September 20, 2013 Time: 12:00 - 12:50 PM Place: Centennial Engineering Center 1041 Abstract: A rigorous understanding of computation in biological regulatory networks needs formal models of chemical algorithmic behavior. Moreover, advances in synthetic biology herald the time when we will be able to rationally engineer complex molecular interactions -- then, such abstract models will become blueprints for engineering. A natural language for describing the interactions of molecular species is that of chemical reaction networks (CRNs), i.e., sets of chemical reactions such as A + B -> A + C. Besides chemistry, CRNs are used to analyze numerous other systems with a large number of interacting components such as animal populations and sensor networks. Indeed, equivalent models repeatedly arise in theoretical computer science (e.g. vector addition systems, petri nets, population protocols). I will overview some of what is known about the algorithmic behavior of CRNs, and segue into our recent work on characterizing "parameter-free" computation. Fascinating questions abound. I will conclude with a description of our efforts to realize CRNs with rationally designed molecules in the test tube. We showed that cascades of nucleic-acid "strand displacement" reactions are powerful enough to implement arbitrary CRNs, and recently experimentally demonstrated proof-of-principle networks. Programming strand displacement systems helps inform our understanding of the general notion of "chemical algorithms". Further, strand displacement cascades could one day be used as embedded control modules for fully artificial biochemical systems, or be inserted into natural biological systems to reprogram their behavior. Short Bio: David Soloveichik received AB and MS degrees (2002) in Computer Science from Harvard, and a PhD degree (2008) in Computation and Neural Systems from Caltech, where his advisor was Erik Winfree. His dissertation on "Self-assembly, Molecular automata, and Chemical Reaction Networks" was awarded the Milton and Francis Clauser Doctoral Prize for the best doctoral thesis at Caltech (2008). He was a Computing Innovation Fellow at the University of Washington, Computer Science & Engineering, and he is currently a Fellow at the UCSF Center for Systems and Synthetic Biology. He received the Feynman Prize in Nanotechnology from the Foresight Institute (2012) for this theoretical work on nucleic-acid strand displacement cascades andchemical computation.
Posted on: Mon, 16 Sep 2013 21:43:01 +0000
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