%0 Journal Article %1 heirendt2019creation %A Heirendt, Laurent %A Arreckx, Sylvain %A Pfau, Thomas %A Mendoza, Sebastián N. %A Richelle, Anne %A Heinken, Almut %A Haraldsdóttir, Hulda S. %A Wachowiak, Jacek %A Keating, Sarah M. %A Vlasov, Vanja %A Magnusdóttir, Stefania %A Ng, Chiam Yu %A Preciat, German %A Žagare, Alise %A Chan, Siu H. J. %A Aurich, Maike K. %A Clancy, Catherine M. %A Modamio, Jennifer %A Sauls, John T. %A Noronha, Alberto %A Bordbar, Aarash %A Cousins, Benjamin %A El Assal, Diana C. %A Valcarcel, Luis V. %A Apaolaza, Iñigo %A Ghaderi, Susan %A Ahookhosh, Masoud %A Ben Guebila, Marouen %A Kostromins, Andrejs %A Sompairac, Nicolas %A Le, Hoai M. %A Ma, Ding %A Sun, Yuekai %A Wang, Lin %A Yurkovich, James T. %A Oliveira, Miguel A. P. %A Vuong, Phan T. %A El Assal, Lemmer P. %A Kuperstein, Inna %A Zinovyev, Andrei %A Hinton, H. Scott %A Bryant, William A. %A Aragón Artacho, Francisco J. %A Planes, Francisco J. %A Stalidzans, Egils %A Maass, Alejandro %A Vempala, Santosh %A Hucka, Michael %A Saunders, Michael A. %A Maranas, Costas D. %A Lewis, Nathan E. %A Sauter, Thomas %A Palsson, Bernhard Ø. %A Thiele, Ines %A Fleming, Ronan M. T. %D 2019 %J Nature Protocols %K cobra constraint-based-modelling flux-analysis software %N 3 %P 639--702 %R 10.1038/s41596-018-0098-2 %T Creation and analysis of biochemical constraint-based models using the COBRA Toolbox v.3.0 %U https://doi.org/10.1038/s41596-018-0098-2 %V 14 %X 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.

@article{heirendt2019creation, 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.}, added-at = {2019-10-08T10:15:44.000+0200}, author = {Heirendt, Laurent and Arreckx, Sylvain and Pfau, Thomas and Mendoza, Sebastián N. and Richelle, Anne and Heinken, Almut and Haraldsdóttir, Hulda S. and Wachowiak, Jacek and Keating, Sarah M. and Vlasov, Vanja and Magnusdóttir, Stefania and Ng, Chiam Yu and Preciat, German and Žagare, Alise and Chan, Siu H. J. and Aurich, Maike K. and Clancy, Catherine M. and Modamio, Jennifer and Sauls, John T. and Noronha, Alberto and Bordbar, Aarash and Cousins, Benjamin and El Assal, Diana C. and Valcarcel, Luis V. and Apaolaza, Iñigo and Ghaderi, Susan and Ahookhosh, Masoud and Ben Guebila, Marouen and Kostromins, Andrejs and Sompairac, Nicolas and Le, Hoai M. and Ma, Ding and Sun, Yuekai and Wang, Lin and Yurkovich, James T. and Oliveira, Miguel A. P. and Vuong, Phan T. and El Assal, Lemmer P. and Kuperstein, Inna and Zinovyev, Andrei and Hinton, H. Scott and Bryant, William A. and Aragón Artacho, Francisco J. and Planes, Francisco J. and Stalidzans, Egils and Maass, Alejandro and Vempala, Santosh and Hucka, Michael and Saunders, Michael A. and Maranas, Costas D. and Lewis, Nathan E. and Sauter, Thomas and Palsson, Bernhard Ø. and Thiele, Ines and Fleming, Ronan M. T.}, biburl = {https://www.bibsonomy.org/bibtex/21017b123a8d05e859c64645810c10baa/karthikraman}, description = {Creation and analysis of biochemical constraint-based models using the COBRA Toolbox v.3.0 | Nature Protocols}, doi = {10.1038/s41596-018-0098-2}, interhash = {c0906e37f8308cf6e84a1e442732bd73}, intrahash = {1017b123a8d05e859c64645810c10baa}, issn = {17502799}, journal = {Nature Protocols}, keywords = {cobra constraint-based-modelling flux-analysis software}, number = 3, pages = {639--702}, refid = {Heirendt2019}, timestamp = {2019-10-08T10:15:44.000+0200}, title = {Creation and analysis of biochemical constraint-based models using the COBRA Toolbox v.3.0}, url = {https://doi.org/10.1038/s41596-018-0098-2}, volume = 14, year = 2019 }