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A simplified metabolic network reconstruction to promote understanding and development of flux balance analysis tools

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December 26 2018
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Comput Biol Med. 2019 Feb;105:64-71. doi: 10.1016/j.compbiomed.2018.12.010. Epub 2018 Dec 17.

ABSTRACT

GEnome-scale Network REconstructions (GENREs) mathematically describe metabolic reactions of an organism or a specific cell type. GENREs can be used with a number of constraint-based reconstruction and analysis (COBRA) methods to make computational predictions on how a system changes in different environments. We created a simplified GENRE (referred to as iSIM) that captures central energy metabolism with nine metabolic reactions to illustrate the use of and promote the understanding of GENREs and constraint-based methods. We demonstrate the simulation of single and double gene deletions, flux variability analysis (FVA), and test a number of metabolic tasks with the GENRE. Code to perform these analyses is provided in Python, R, and MATLAB. Finally, with iSIM as a guide, we demonstrate how inaccuracies in GENREs can limit their use in the interrogation of energy metabolism.

PMID:30584952 | DOI:10.1016/j.compbiomed.2018.12.010

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Computational Systems Biology Laboratory; The research group of Dr. Jason Papin in the Department of Biomedical Engineering at the University of Virginia.

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The research group of Dr. Jason Papin in the Department of Biomedical Engineering at the University of Virginia

  • Email: papinlab@virginia.edu
  • Phone (434) 924-8195

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  • Meet Our Team
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