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Open AccessJournal ArticleDOI

Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox v2.0

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.

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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

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.
References
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Journal ArticleDOI

Cytoscape: A Software Environment for Integrated Models of Biomolecular Interaction Networks

TL;DR: Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.
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KEGG: Kyoto Encyclopedia of Genes and Genomes

TL;DR: The Kyoto Encyclopedia of Genes and Genomes (KEGG) as discussed by the authors is a knowledge base for systematic analysis of gene functions in terms of the networks of genes and molecules.
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The KEGG resource for deciphering the genome

TL;DR: A knowledge-based approach for network prediction is developed, which is to predict, given a complete set of genes in the genome, the protein interaction networks that are responsible for various cellular processes.
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The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models.

TL;DR: This work summarizes the Systems Biology Markup Language (SBML) Level 1, a free, open, XML-based format for representing biochemical reaction networks, a software-independent language for describing models common to research in many areas of computational biology.
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