Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox v2.0
Open accessAbstract
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.
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ecYeast7 is fully compatible with the COBRA toolbox and has similar simulation running times compared to Yeast7, with a standard growth maximization FBA problem solved in 135 ± 7.3 ms versus 138 ± 9.7 ms.
“Finally, ecYeast7 is fully compatible with the COBRA toolbox (Schellenberger et al, 2011) and has similar simulation running times compared to its metabolic counterpart: A standard growth maximization FBA problem of ecYeast7 is solved in 135 ± 7.3 ms with the Gurobi LP solver in a Windows PC with a 2.1 GHz Intel i7‐4600U two processor, compared to 138 ± 9.7 ms in the case of Yeast7.”
From Improving the phenotype predictions of a yeast genome‐scale metabolic model by incorporating enzymatic constraints (2017) · cites this paper as Schellenberger et al, 2011
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- Authors
- Schellenberger, J., Que, R., Fleming, R. M. T., Thiele, I., Orth, J. D., Feist, A. M., Zielinski, D. C., Bordbar, A., Lewis, N. E., Rahmanian, S., Kang, J., Hyduke, D. R., & Palsson, B. Ø.
- Affiliations
- University of California San Diego (US)
- University of Iceland (IS)
- Corresponding author
- Hyduke, Daniel R
- Palsson, Bernhard Ø
- ORCID
- Venue
- Nature Protocols
- Published
- 2011-08-04
- Volume
- 6
- Issue
- 9
- Pages
- 1290-1307
- ISSN
- 1750-2799 (ISSN-L)
- 1754-2189
- PMC
- PMC3319681
- OpenAlex
- W2147472054
- Cited by
- 1,835
- References
- 89
- Citations by year
- 2026: 16 · 2025: 25 · 2024: 46 · 2023: 48 · 2022: 53 · 2021: 93 · 2020: 98 · 2019: 146 · 2018: 159 · 2017: 186 · 2016: 151 · 2015: 163 · 2014: 166 · 2013: 134 · 2012: 127
- FWCI
- 66.03
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature Protocols (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Open Repository and Bibliography (University of Luxembourg) (submittedVersion, cc-by-nc-sa)
- Funders
- National Institute of General Medical Sciences (GM68837-05A1, R01GM068837, R01GM057089, GM057089-11S1)
- National Institute of Allergy and Infectious Diseases (Y1-AI8401-01, Y01 AI008401)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Microbial Metabolic Engineering and Bioproduction
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Keywords
- COBRA toolbox, constraint-based metabolic modeling, genome-scale metabolic models, metabolic engineering, SBML, metabolic phenotypes
- MeSH terms
- Algorithms, Software, Computational Biology, Metabolic Networks and Pathways
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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