Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox v2.0

• Published in: Nature protocols Vol. 6; no. 9; pp. 1290 - 1307
• Main Authors: Schellenberger, Jan, Que, Richard, Fleming, Ronan M T, Thiele, Ines, Orth, Jeffrey D, Feist, Adam M, Zielinski, Daniel C, Bordbar, Aarash, Lewis, Nathan E, Rahmanian, Sorena, Kang, Joseph, Hyduke, Daniel R, Palsson, Bernhard Ø
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 01.09.2011; Nature Publishing Group
• Subjects: 631/114; 631/1647/320; Algorithms; Analytical Chemistry; Biological Techniques; Biology; Biomedical and Life Sciences; Computational Biology - methods; Computational Biology/Bioinformatics; Documentation; Engineering; Gene loci; Genomes; Life Sciences; Metabolic Networks and Pathways; Metabolism; Microarrays; Organic Chemistry; Proteins; Protocol; Scale models; Software; United States; La Jolla California; California; United States > US; Iceland
• ISSN: 1754-2189; 1750-2799; 1750-2799
• DOI: 10.1038/nprot.2011.308

Over the past decade, a growing community of researchers has emerged around the use of constraint-based reconstruction and analysis (COBRA) methods to simulate, analyze and predict a variety of metabolic phenotypes using genome-scale models. The COBRA Toolbox, a MATLAB package for implementing COBRA methods, was presented earlier. Here we present a substantial update of this in silico toolbox. Version 2.0 of the COBRA Toolbox expands the scope of computations by including in silico analysis methods developed since its original release. New functions include (i) network gap filling, (ii) 13 C analysis, (iii) metabolic engineering, (iv) omics-guided analysis and (v) visualization. As with the first version, the COBRA Toolbox reads and writes systems biology markup language–formatted models. In version 2.0, we improved performance, usability and the level of documentation. A suite of test scripts can now be used to learn the core functionality of the toolbox and validate results. This toolbox lowers the barrier of entry to use powerful COBRA methods.