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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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.
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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.
Journal ArticleDOI
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.
Journal ArticleDOI
Acidithiobacillus ferrooxidans's comprehensive model driven analysis of the electron transfer metabolism and synthetic strain design for biomining applications.
Miguel A. Campodonico,Daniela Vaisman,Jean Franco Castro,Valeria Razmilic,Francesca Mercado,Barbara A. Andrews,Adam M. Feist,Juan A. Asenjo +7 more
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.
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