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Creation and analysis of biochemical constraint-based models using the COBRA Toolbox v.3.0

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Heirendt, Laurent, Arreckx, Sylvain, Pfau, Thomas, Mendoza, Sebastián N., Richelle, Anne, Heinken, Almut, Haraldsdóttir, Hulda S., Wachowiak, Jacek, Keating, Sarah M., Vlasov, Vanja, Magnusdóttir, Stefania, Ng, Chiam Yu, Preciat, German, Žagare, Alise, Chan, Siu H. J., Aurich, Maike K., Clancy, Catherine M., Modamio, Jennifer, Sauls, John T., Noronha, Alberto, Bordbar, Aarash, Cousins, Benjamin, El Assal, Diana C., Valcarcel, Luis V., Apaolaza, Iñigo, Ghaderi, Susan, Ahookhosh, Masoud, Ben Guebila, Marouen, Kostromins, Andrejs, Sompairac, Nicolas, Le, Hoai M., Ma, Ding, Sun, Yuekai, Wang, Lin, Yurkovich, James T., Oliveira, Miguel A. P., Vuong, Phan T., El Assal, Lemmer P., Kuperstein, Inna, Zinovyev, Andrei, Hinton, H. Scott, Bryant, William A., Aragón Artacho, Francisco J., Planes, Francisco J., Stalidzans, Egils, Maass, Alejandro, Vempala, Santosh, Hucka, Michael, Saunders, Michael A., Maranas, Costas D., Lewis, Nathan E., Sauter, Thomas, Palsson, Bernhard Ø., Thiele, Ines, Fleming, Ronan M. T.·2019·Nature Protocols
DOI 10.1038/s41596-018-0098-2
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Abstract

Constraint-based reconstruction and analysis (COBRA) provides a molecular mechanistic framework for integrative analysis of experimental molecular systems biology data and quantitative prediction of physicochemically and biochemically feasible phenotypic states. The COBRA Toolbox is a comprehensive desktop software suite of interoperable COBRA methods. It has found widespread application in biology, biomedicine, and biotechnology because its functions can be flexibly combined to implement tailored COBRA protocols for any biochemical network. This protocol is an update to the COBRA Toolbox v.1.0 and v.2.0. Version 3.0 includes new methods for quality-controlled reconstruction, modeling, topological analysis, strain and experimental design, and network visualization, as well as network integration of chemoinformatic, metabolomic, transcriptomic, proteomic, and thermochemical data. New multi-lingual code integration also enables an expansion in COBRA application scope via high-precision, high-performance, and nonlinear numerical optimization solvers for multi-scale, multi-cellular, and reaction kinetic modeling, respectively. This protocol provides an overview of all these new features and can be adapted to generate and analyze constraint-based models in a wide variety of scenarios. The COBRA Toolbox v.3.0 provides an unparalleled depth of COBRA methods. The COBRA toolbox provides quality-controlled reconstruction, modeling, topological analysis, and network visualization, as well as network integration of chemoinformatic, metabolomic, transcriptomic, proteomic, and thermochemical data.

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Cited by

Metadata

Authors
Heirendt, L., Arreckx, S., Pfau, T., Mendoza, S. N., Richelle, A., Heinken, A., Haraldsdóttir, H. S., Wachowiak, J., Keating, S. M., Vlasov, V., Magnusdóttir, S., Ng, C. Y., Preciat, G., Žagare, A., Chan, S. H. J., Aurich, M. K., Clancy, C. M., Modamio, J., Sauls, J. T., Noronha, A., Bordbar, A., Cousins, B., El Assal, D. C., Valcarcel, L. V., Apaolaza, I., Ghaderi, S., Ahookhosh, M., Ben Guebila, M., Kostromins, A., Sompairac, N., Le, H. M., Ma, D., Sun, Y., Wang, L., Yurkovich, J. T., Oliveira, M. A. P., Vuong, P. T., El Assal, L. P., Kuperstein, I., Zinovyev, A., Hinton, H. S., Bryant, W. A., Aragón Artacho, F. J., Planes, F. J., Stalidzans, E., Maass, A., Vempala, S., Hucka, M., Saunders, M. A., Maranas, C. D., Lewis, N. E., Sauter, T., Palsson, B. Ø., Thiele, I., & Fleming, R. M. T.
Venue
Nature Protocols
Publisher
Springer Science and Business Media LLC
Published
2019-02-20
Volume
14
Issue
3
Pages
639-702
ISSN
  • 1750-2799 (ISSN-L)
  • 1754-2189
DOI
10.1038/s41596-018-0098-2
OpenAlex
W2762019694
Cited by
1,242
References
13
FWCI
40.96
Type
journal article
Language
en
Open access
green
Licence

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.