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

By Jan Schellenberger, Richard A Que, Ronan M. T. Fleming, Ines Thiele, Jeffrey D. Orth, Adam M. Feist, Daniel C. Zielinski, Aarash Bordbar, Nathan E. Lewis, Sorena Rahmanian and 3 more. Nature Protocols, 2007

1,776 citations recorded by the source corpus.

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) 13C 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.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/26084f2a0e12cad7136fc98d55d2aea592590958

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Citations in the corpus

Computationally efficient flux variability analysis (2010, methodology): “The running times are given in Table 2 where fastFVA is compared to the direct implementation of FVA found in the COBRA toolbox [10].”
Improving the phenotype predictions of a yeast genome‐scale metabolic model by incorporating enzymatic constraints (2017, methodology): “Both GECKO and ecYeast7 are compatible with the COBRA toolbox (Schellenberger et al, 2011) or any constraint-based approach.”
Integrative approaches for finding modular structure in biological networks (2013, methodology): “A version of the application tool COBRA (constraint-based reconstruction and analysis) (TABLE 1) permits omics-constrained analyses of genome-scale metabolic networks to predict feasible metabolic phenotypes and relevant modules under a given set of conditions 85 .”
Consistent Estimation of Gibbs Energy Using Component Contributions (2013, methodology): “It is fully compatible with the COBRA toolbox [40] and is freely available as part of the openCOBRA project on Sourceforge (http://sourceforge.”
A protocol for generating a high-quality genome-scale metabolic reconstruction (2010, methodology): “Matlab was also used to encode the COBRA Toolbox, which is a suite of COBRA functions commonly used for simulation”
Reconstruction of Biochemical Networks in Microbial Organisms (2008, methodology): “, and computational methods and tools used to characterize them have been reviewe”
BiGG Models: A platform for integrating, standardizing and sharing genome-scale models (2015, methodology): “Models are available in MATLAB MAT format for analysis with the MATLAB COBRA toolbox (33) and the JavaScript Object Notation (JSON) format for building visualizations with Escher (24).”
COBRApy: COnstraints-Based Reconstruction and Analysis for Python (2013, methodology): “We have previously published the COBRA Toolbox [19] for MATLAB to provide systems biology researchers with a high-level interface to a variety of methods for constraint-based modeling of genome-scale stoichiometric models of cellular biochemistry.”
A white-box machine learning approach for revealing antibiotic mechanisms of action (2019, positive): “—Metabolic simulations were performed using the COBRA Toolbox v. 2.0 (Schellenberger et al., 2011) in MATLAB and Gurobi Optimizer v. 6.0.4 (Gurobi Optimization; Beaverton, OR).”
RAVEN 2.0: A versatile toolbox for metabolic network reconstruction and a case study on Streptomyces coelicolor (2018, methodology): “As such, the RAVEN toolbox has functioned as one of the two major MATLAB-based packages for constraint-based metabolic modelling, together with the COBRA Toolbox [23–25].”
BiGG: a Biochemical Genetic and Genomic knowledgebase of large scale metabolic reconstructions (2010, methodology): “SBML files conform to the level 2 version 1 specification and are compatible with the COBRA toolbox [ 47 ] which contains many computational procedures.”
Applications of genome-scale metabolic reconstructions (2009, background): “Feist et al , 2009 ) and several resources exist for model building and analysis”
OptFlux: an open-source software platform for in silico metabolic engineering (2010, methodology): “FluxAnalyzer [11] and MetaFluxNet [12], recently the CellNetAnalyzer [13] (the successor of FluxAnalyzer), the COBRA toolbox [ 14 ] and the Systems Biology Research Tool (SBRT) [15] have been launched.”
Creation and analysis of biochemical constraint-based models: the COBRA Toolbox v3.0 (2019, background): “Once procedure [4] is concluded, all changes on the deleted branch are removed, both locally and remotely.”
A comprehensive genome-scale reconstruction of Escherichia coli metabolism—2011 (2011, background): “A network reconstruction represents a biochemically, genetically, and genomically structured knowledgebase that contains detailed information about an organism in a structured format”