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DTSTAMP:20200122T145806Z
CREATED:20191119T152055Z
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UID:10384504-1580484600-1580488200@uwm.edu
SUMMARY:Physics Colloquium - Andrew Ferguson
DESCRIPTION:Andrew Ferguson\, University of Chicago \nReconstructing All-Atom Protein Folding from Low-Dimensional Experimental Time Series \nData-driven modeling and machine learning present powerful tools that are opening up new paradigms and opportunities in the understanding\, discovery\, and design of soft and biological materials.  In the first part of this talk\, I will describe an approach integrating ideas from dynamical systems theory and nonlinear manifold learning to reconstruct multidimensional protein folding funnels from the time evolution of single experimentally measurable observables. In the second part of this talk\, I will describe our use of deep learning to estimate slow collective variables from molecular simulation trajectories and the use of these coordinates to train highly efficient latent space molecular simulators. By combining these two ideas it is possible to reconstruct all-atom molecular configurations from one-dimensional time series in experimentally measurable observables. \nEvent flyer is available here
URL:https://uwm.edu/physics/event/physics-colloquium-andrew-ferguson/
LOCATION:Lapham 160\, 3209 N. Maryland Ave.\, Milwaukee\, WI\, 53211\, United States
CATEGORIES:Physics Colloquia
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