Literature DB >> 30787451

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

Laurent Heirendt1, Sylvain Arreckx1, Thomas Pfau2, Sebastián N Mendoza3,4, Anne Richelle5, Almut Heinken1, Hulda S Haraldsdóttir1, Jacek Wachowiak1, Sarah M Keating6, Vanja Vlasov1, Stefania Magnusdóttir1, Chiam Yu Ng7, German Preciat1, Alise Žagare1, Siu H J Chan7, Maike K Aurich1, Catherine M Clancy1, Jennifer Modamio1, John T Sauls8, Alberto Noronha1, Aarash Bordbar9, Benjamin Cousins10, Diana C El Assal1, Luis V Valcarcel11, Iñigo Apaolaza11, Susan Ghaderi1, Masoud Ahookhosh1, Marouen Ben Guebila1, Andrejs Kostromins12, Nicolas Sompairac13, Hoai M Le1, Ding Ma14, Yuekai Sun15, Lin Wang7, James T Yurkovich16, Miguel A P Oliveira1, Phan T Vuong1, Lemmer P El Assal1, Inna Kuperstein13, Andrei Zinovyev13, H Scott Hinton17, William A Bryant18, Francisco J Aragón Artacho19, Francisco J Planes11, Egils Stalidzans12, Alejandro Maass3,4, Santosh Vempala10, Michael Hucka20, Michael A Saunders14, Costas D Maranas7, Nathan E Lewis5,21, Thomas Sauter2, Bernhard Ø Palsson16,22, Ines Thiele1, Ronan M T Fleming23,24.   

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.

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Year:  2019        PMID: 30787451      PMCID: PMC6635304          DOI: 10.1038/s41596-018-0098-2

Source DB:  PubMed          Journal:  Nat Protoc        ISSN: 1750-2799            Impact factor:   13.491


  119 in total

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Authors:  Paulo Maia; Miguel Rocha; Isabel Rocha
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2.  Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox.

Authors:  Scott A Becker; Adam M Feist; Monica L Mo; Gregory Hannum; Bernhard Ø Palsson; Markus J Herrgard
Journal:  Nat Protoc       Date:  2007       Impact factor: 13.491

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Authors:  Neema Jamshidi; Bernhard Ø Palsson
Journal:  Blood Cells Mol Dis       Date:  2006-03-13       Impact factor: 3.039

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Authors:  Edward J O'Brien; Jonathan M Monk; Bernhard O Palsson
Journal:  Cell       Date:  2015-05-21       Impact factor: 41.582

Review 6.  Constraint-based models predict metabolic and associated cellular functions.

Authors:  Aarash Bordbar; Jonathan M Monk; Zachary A King; Bernhard O Palsson
Journal:  Nat Rev Genet       Date:  2014-01-16       Impact factor: 53.242

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Journal:  Cell Syst       Date:  2016-11-23       Impact factor: 10.304

8.  Mammalian Systems Biotechnology Reveals Global Cellular Adaptations in a Recombinant CHO Cell Line.

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Journal:  Cell Syst       Date:  2017-05-24       Impact factor: 10.304

9.  Genome-scale dynamic modeling of the competition between Rhodoferax and Geobacter in anoxic subsurface environments.

Authors:  Kai Zhuang; Mounir Izallalen; Paula Mouser; Hanno Richter; Carla Risso; Radhakrishnan Mahadevan; Derek R Lovley
Journal:  ISME J       Date:  2010-07-29       Impact factor: 10.302

10.  A protocol for generating a high-quality genome-scale metabolic reconstruction.

Authors:  Ines Thiele; Bernhard Ø Palsson
Journal:  Nat Protoc       Date:  2010-01-07       Impact factor: 13.491

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  217 in total

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Journal:  ISME J       Date:  2020-04-29       Impact factor: 10.302

2.  Metabolic network percolation quantifies biosynthetic capabilities across the human oral microbiome.

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Journal:  Elife       Date:  2019-06-13       Impact factor: 8.140

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4.  Flux balance analysis of cyanobacteria reveals selective use of photosynthetic electron transport components under different spectral light conditions.

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6.  Genome-Scale Identification of Essential Metabolic Processes for Targeting the Plasmodium Liver Stage.

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Journal:  Cell       Date:  2019-11-14       Impact factor: 41.582

7.  A mechanism-aware and multiomic machine-learning pipeline characterizes yeast cell growth.

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8.  An atlas of human metabolism.

Authors:  Jonathan L Robinson; Pınar Kocabaş; Hao Wang; Pierre-Etienne Cholley; Daniel Cook; Avlant Nilsson; Mihail Anton; Raphael Ferreira; Iván Domenzain; Virinchi Billa; Angelo Limeta; Alex Hedin; Johan Gustafsson; Eduard J Kerkhoven; L Thomas Svensson; Bernhard O Palsson; Adil Mardinoglu; Lena Hansson; Mathias Uhlén; Jens Nielsen
Journal:  Sci Signal       Date:  2020-03-24       Impact factor: 8.192

9.  FastMM: an efficient toolbox for personalized constraint-based metabolic modeling.

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Journal:  BMC Bioinformatics       Date:  2020-02-21       Impact factor: 3.169

10.  Complete genome sequence and genome-scale metabolic modelling of Acinetobacter baumannii type strain ATCC 19606.

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Journal:  Int J Med Microbiol       Date:  2020-02-05       Impact factor: 3.473

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