473979 Towards Systems-Scale Dynamic Metabolic Modeling

Monday, November 14, 2016: 1:45 PM
Carmel I (Hotel Nikko San Francisco)
Mark P. Styczynski, School of Chemical and Biomolecular Engineering, Georgia Institute of Technology, Atlanta, GA and Robert Dromms, Chemical & Biomolecular Engineering, Georgia Institute of Technology, Atlanta, GA

Here we present recent efforts to create genome-scale, dynamic metabolic modeling methods that utilize a form of systems-scale data that is of rising importance: metabolomics. Metabolomics data have all too often been omitted from metabolic engineering and other related analyses of metabolism, in part because most systems-scale models of metabolism assume a pseudo-steady state and thus limit the time variability of metabolite levels. Here we explore new ways to include this data that help to drive the development of computational approaches that may ultimately allow for genome-scale dynamic metabolic models. Creating such models would be critical advance for numerous fields including metabolic engineering, allowing in silico modeling even when experimental evolution work is not feasible.

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