Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox v2.0
Jan Schellenberger,Richard Que,Ronan M. T. Fleming,Ines Thiele,Jeffrey D. Orth,Adam M. Feist,Daniel C. Zielinski,Aarash Bordbar,Nathan E. Lewis,Sorena Rahmanian,Joseph Kang,Daniel R. Hyduke,Bernhard O. Palsson +12 more
TLDR
The constraint-based reconstruction and analysis toolbox as discussed by the authors is a software package running in the Matlab environment, which allows for quantitative prediction of cellular behavior using a constraintbased approach and allows predictive computations of both steady-state and dynamic optimal growth behavior, the effects of gene deletions, comprehensive robustness analyses, sampling the range of possible cellular metabolic states and the determination of network modules.Abstract:
The manner in which microorganisms utilize their metabolic processes can be predicted using constraint-based analysis of genome-scale metabolic networks. Herein, we present the constraint-based reconstruction and analysis toolbox, a software package running in the Matlab environment, which allows for quantitative prediction of cellular behavior using a constraint-based approach. Specifically, this software allows predictive computations of both steady-state and dynamic optimal growth behavior, the effects of gene deletions, comprehensive robustness analyses, sampling the range of possible cellular metabolic states and the determination of network modules. Functions enabling these calculations are included in the toolbox, allowing a user to input a genome-scale metabolic model distributed in Systems Biology Markup Language format and perform these calculations with just a few lines of code. The results are predictions of cellular behavior that have been verified as accurate in a growing body of research. After software installation, calculation time is minimal, allowing the user to focus on the interpretation of the computational results.read more
Citations
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ReconMap: an interactive visualization of human metabolism.
Alberto Noronha,Anna Dröfn Daníelsdóttir,Piotr Gawron,Freyr Jóhannsson,Soffia Jónsdóttir,Sindri Jarlsson,Jón Pétur Gunnarsson,Sigurður Brynjólfsson,Reinhard Schneider,Ines Thiele,Ronan M. T. Fleming +10 more
TL;DR: A comprehensive map is drawn that is consistent with the content of Recon 2.0 and presented within a web interface that allows content query, visualization of custom datasets and submission of feedback to manual curators.
Journal ArticleDOI
Decomposing complex reaction networks using random sampling, principal component analysis and basis rotation
TL;DR: This work shows how the top-down analysis of networks can be used to determine key regulatory requirements independent of specific parameters and mechanisms, and complements the reductionist approach to elucidation of regulatory mechanisms and facilitates the development of the understanding of global regulatory strategies in biological networks.
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Modelling cyanobacteria: from metabolism to integrative models of phototrophic growth
TL;DR: The focus of the contribution is on a mathematical description of the metabolic network of Synechocystis sp.
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A conceptual review on systems biology in health and diseases: from biological networks to modern therapeutics
TL;DR: A concept of cell-to-human framework comprising of five modules ( data mining, networking, modeling, experimental and validation) for addressing human physiology and diseases based on a paradigm of system level analysis is put forth.
Journal ArticleDOI
Methods for automated genome-scale metabolic model reconstruction
TL;DR: Comparing and contrasting the capabilities and output of a variety of tools for rapid automated reconstruction of metabolic models, including ModelSEED, Raven Toolbox, PathwayTools, SuBliMinal Toolbox and merlin.
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