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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Journal ArticleDOI
Enhancement of rapamycin production by metabolic engineering in Streptomyces hygroscopicus based on genome-scale metabolic model
TL;DR: The relationship between model prediction and experimental results demonstrates the validity and rationality of this approach for target identification and rapamycin production improvement.
Journal ArticleDOI
Flux balance analysis of cyanobacteria reveals selective use of photosynthetic electron transport components under different spectral light conditions
TL;DR: To predict the detailed electron transfer flux of cyanobacteria, the photosynthesis-related reactions in the previously reconstructed genome-scale model were refined and functionally implicatedNDH-1 and NDH-2 as a component of cyclic electron transport in the varied light environments.
Journal ArticleDOI
An enhanced genome-scale metabolic reconstruction of Streptomyces clavuligerus identifies novel strain improvement strategies
TL;DR: A genome-scale metabolic model of Streptomyces clavuligerus was expanded and updated and a strain design was carried out to identify candidate genes to be overexpressed or knocked out so as to maximize antibiotic biosynthesis.
Book ChapterDOI
Directed multistep biocatalysis using tailored permeabilized cells.
TL;DR: An extended review of useful available databases and bioinformatics tools, particularly for setting up genome-scale reconstructed networks, and methods for the permeabilization of cells are thoroughly reviewed.
Book ChapterDOI
Genome-scale metabolic models of Saccharomyces cerevisiae.
TL;DR: In this chapter, the principle concepts for construction, simulation and validation of GSM models, progressive applications of the yeast G SM models, and future perspectives are described to support and encourage researchers who are interested in systemic analysis of yeast metabolism and systems biology.
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