Creation and analysis of biochemical constraint-based models using the COBRA Toolbox v.3.0
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Published:2019-02-20
Issue:3
Volume:14
Page:639-702
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ISSN:1754-2189
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Container-title:Nature Protocols
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language:en
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Short-container-title:Nat Protoc
Author:
Heirendt Laurent, Arreckx Sylvain, Pfau ThomasORCID, Mendoza Sebastián N.ORCID, 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.ORCID, Apaolaza IñigoORCID, Ghaderi Susan, Ahookhosh Masoud, Ben Guebila Marouen, Kostromins Andrejs, Sompairac Nicolas, Le Hoai M., Ma Ding, Sun Yuekai, Wang Lin, Yurkovich James T.ORCID, Oliveira Miguel A. P., Vuong Phan T., El Assal Lemmer P., Kuperstein InnaORCID, 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.ORCID, Sauter Thomas, Palsson Bernhard Ø., Thiele Ines, Fleming Ronan M. T.
Publisher
Springer Science and Business Media LLC
Subject
General Biochemistry, Genetics and Molecular Biology
Reference155 articles.
1. Palsson, B. Ø. Systems Biology: Constraint-Based Reconstruction and Analysis (Cambridge University Press, Cambridge, 2015). 2. O’Brien, E. J., Monk, J. M. & Palsson, B. O. Using genome-scale models to predict biological capabilities. Cell 161, 971–987 (2015). 3. Becker, S. A. et al. Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox. Nat. Protoc. 2, 727–738 (2007). 4. Schellenberger, J. et al. Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox v2.0. Nat. Protoc. 6, 1290–1307 (2011). 5. Lewis, N. E., Nagarajan, H. & Palsson, B. O. Constraining the metabolic genotype–phenotype relationship using a phylogeny of in silico methods. Nat. Rev. Microbiol. 10, 291–305 (2012).
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