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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Dynamic flux balance analysis of biomass and lipid production by Antarctic thraustochytrid Oblongichytrium sp. RT2316-13.
TL;DR: Both a simple minimally structured mathematical model and a more complex genome‐scale metabolic model allowed the fermentation profiles in batch cultures to be satisfactorily simulated, but the GEM provided much greater insight in the biochemical and physiological phenomena underlying the observed behavior.
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Construction of polyketide overproducing Escherichia coli strains via synthetic antisense RNAs based on in silico fluxome analysis and comparative transcriptome analysis.
TL;DR: A systematic approach to characterize the module interactions and improve the problematic modules during the 6-deoxyerythronolide B (6dEB) biosynthesis in E. coli is developed and the effectiveness of antisense RNA for use in metabolic engineering is indicated.
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Solving Puzzles With Missing Pieces: The Power of Systems Biology
TL;DR: A first principles ``bottom-up'' approach to systems biology rooted in fundamental mechanisms has arisen, and the quest to reveal the program that DNA encodes is underway.
Journal ArticleDOI
Application of string similarity ratio and edit distance in automatic metabolite reconciliation comparing reconstructions and models
Martins Mednis,Maike K. Aurich +1 more
TL;DR: A model comparison algorithm for SBML and COBRA format models is presented, called ModeRator, which rejects pairs of potentially equal metabolites and builds an opinion about metabolite pairs with high similarity in metabolite names.
Journal ArticleDOI
Genome-wide metabolic model to improve understanding of CD4+ T cell metabolism, immunometabolism and application in drug design
TL;DR: This work reconstructed the genome-wide metabolic network of naïve CD4(+) T cells, CD4T1670, by integrating transcriptome and metabolism data and found that depletion of either glucose or glutamine did not significantly affect ATP production and biomass, but dramatically unbalanced the metabolic network and increased the release of some inflammation or anti-inflammation related factors.
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