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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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Rapid media transition: An experimental approach for steady state analysis of metabolic pathways

TL;DR: Extracellular rates and metabolome data indicate a metabolic steady state during the short‐term cultivation, and Stoichiometric analysis revealed distribution of intracellular fluxes, which differs drastically subject to the applied carbon source.
Journal ArticleDOI

KiMoSys: a web-based repository of experimental data for KInetic MOdels of biological SYStems.

TL;DR: Ki MoSys is a web-based system that integrates a public data and associated model(s) repository with computational tools, providing the systems biology community with a novel application facilitating data storage and sharing, thus supporting construction of ODE-based kinetic models and collaborative research projects.
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Genome-scale reconstruction and in silico analysis of Aspergillus terreus metabolism

TL;DR: A genome-scale metabolic model, iJL1454, consisting of 1454 genes, 1451 reactions and 1155 metabolites, based on genome annotation and literature mining is reconstructed, which accurately predicted the growth phenotype of A. terreus on different carbon and nitrogen sources, and after deletion of essential genes.
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Acidithiobacillus ferrooxidans's comprehensive model driven analysis of the electron transfer metabolism and synthetic strain design for biomining applications.

TL;DR: In this study, the first genome-scale metabolic reconstruction of A. ferrooxidans ATCC 23270 was generated and the first genetic algorithm approach, that integrates flux balance analysis, chemiosmotic theory, and physiological data, is applied.
Journal ArticleDOI

Improving the accuracy of flux balance analysis through the implementation of carbon availability constraints for intracellular reactions.

TL;DR: A new, computationally efficient approach that refines flux range predictions by constraining reaction fluxes on the basis of the elemental balance of carbon, ccFBA, which can be used as a stand‐alone method but is also compatible with and complimentary to other constraint‐based approaches.
References
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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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