Missouri University of Science and Technology Scholars' Mine Chemical and Biochemical Engineering Faculty Linda and Bipin Doshi Department of Chemical Research & Creative Works and Biochemical Engineering 01 Oct 2010 An Automated Phenotype-Driven Approach (GeneForce) for Refining Metabolic and Regulatory Models Dipak Barua Missouri University of Science and Technology,
[email protected] Joonhoon Kim Jennifer L. Reed Follow this and additional works at: https://scholarsmine.mst.edu/che_bioeng_facwork Part of the Chemical Engineering Commons Recommended Citation D. Barua et al., "An Automated Phenotype-Driven Approach (GeneForce) for Refining Metabolic and Regulatory Models," PLoS Computational Biology, vol. 6, no. 10, PLoS ONE, Oct 2010. The definitive version is available at https://doi.org/10.1371/journal.pcbi.1000970 This work is licensed under a Creative Commons Attribution 4.0 License. This Article - Journal is brought to you for free and open access by Scholars' Mine. It has been accepted for inclusion in Chemical and Biochemical Engineering Faculty Research & Creative Works by an authorized administrator of Scholars' Mine. This work is protected by U. S. Copyright Law. Unauthorized use including reproduction for redistribution requires the permission of the copyright holder. For more information, please contact
[email protected]. An Automated Phenotype-Driven Approach (GeneForce) for Refining Metabolic and Regulatory Models Dipak Barua1,2., Joonhoon Kim1,2., Jennifer L. Reed1,2* 1 Department of Chemical and Biological Engineering, University of Wisconsin-Madison, Madison, Wisconsin, United States of America, 2 DOE Great Lakes Bioenergy Research Center, University of Wisconsin-Madison, Madison, Wisconsin, United States of America Abstract Integrated constraint-based metabolic and regulatory models can accurately predict cellular growth phenotypes arising from genetic and environmental perturbations.