Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox

• Published in: Nature protocols Vol. 2; no. 3; pp. 727 - 738
• Main Authors: Herrgard, Markus J, Becker, Scott A, Feist, Adam M, Mo, Monica L, Hannum, Gregory, Palsson, Bernhard Ø
• Format: Journal Article
• Language: English
• Published: England Nature Publishing Group 01.03.2007
• Subjects: Bioengineering; Cell metabolism; Cells - metabolism; Computational biology; Computational Biology - methods; Computer Simulation; Genes; Genomes; Glucose; Hypotheses; Metabolic Networks and Pathways - physiology; Metabolism; Metabolites; Methods; Microorganisms; Models, Biological; Physiological aspects; Software; Systems Biology - methods; United States
• ISSN: 1750-2799; 1754-2189; 1750-2799
• DOI: 10.1038/nprot.2007.99

The manner in which microorganisms utilize their metabolic processes can be predicted using constraint-based analysis of genome-scale metabolic networks. Herein, we present the constraint-based reconstruction and analysis toolbox, a software package running in the Matlab environment, which allows for quantitative prediction of cellular behavior using a constraint-based approach. Specifically, this software allows predictive computations of both steady-state and dynamic optimal growth behavior, the effects of gene deletions, comprehensive robustness analyses, sampling the range of possible cellular metabolic states and the determination of network modules. Functions enabling these calculations are included in the toolbox, allowing a user to input a genome-scale metabolic model distributed in Systems Biology Markup Language format and perform these calculations with just a few lines of code. The results are predictions of cellular behavior that have been verified as accurate in a growing body of research. After software installation, calculation time is minimal, allowing the user to focus on the interpretation of the computational results.