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Presenter: Milo Lin, Assistant Professor, Department of Bioinformatics, University of Texas Southwestern Medical Center
Abstract: Equilibrium theory does not describe most of molecular biology, which has limited our ability to extract general principles about living systems. I will discuss a generalization of the Boltzmann distribution to non-equilibrium systems, which turns out to be mathematically equivalent to circuits that obey Ohm's law. We use this framework to derive general properties and performance limits of complex biomolecular systems, including kinetic proofreading and signaling networks, without needing to know their parameter details. More generally, we use this framework to establish more universal design principles, including the maximum efficiency of any chemical engine and the minimum thermodynamic cost of any biomolecular computation. Experimental and numerical data suggest that biological systems operate at the limits allowed by the theory.
Short bio: I am interested in developing theoretical and computational methods to compress the apparent complexity of biomolecular systems. This includes an axiomatic approach based on statistical mechanics and molecular simulations and an informatics approach consisting of an interpretable neural network model.
Host: Dr. Steven Schwartz