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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Insights into metabolic efficiency from flux analysis.
Xuewen Chen,Yair Shachar-Hill +1 more
TL;DR: Insight into the basis of efficiency provided by (13)C-based metabolic flux analysis (MFA) as well as the uses and limitations of efficiency in predictive flux balance analysis (FBA) are highlighted.
Journal ArticleDOI
Systems biology of bacterial nitrogen fixation: High-throughput technology and its integrative description with constraint-based modeling
Osbaldo Resendis-Antonio,Magdalena Hernández,Emmanuel Salazar,Sandra Contreras,Gabriel Martínez Batallar,Yolanda Mora,Sergio Encarnación +6 more
TL;DR: This approach leads to construct a computational model that serves as a guide for integrating high-throughput data, describing and predicting metabolic activity, and designing experiments to explore the genotype-phenotype relationship in bacterial nitrogen fixation.
Journal ArticleDOI
A method for analysis and design of metabolism using metabolomics data and kinetic models: Application on lipidomics using a novel kinetic model of sphingolipid metabolism.
Georgios Savoglidis,Aline X.S. Santos,Isabelle Riezman,Paolo Angelino,Howard Riezman,Vassily Hatzimanikatis +5 more
TL;DR: A model-based method which can be used in conjunction with classical Metabolic Control Analysis for the analysis and design of cellular metabolism, and the class of enzymes regulating the distribution of sphingolipids among species and hydroxylation states is identified.
Journal ArticleDOI
MetaboTools: A comprehensive toolbox for analysis of genome-scale metabolic models
TL;DR: The MetaboTools constitute a comprehensive guide to the intra-model analysis of extracellular metabolomic data from microbial, plant, or human cells and offers a broad set of computational analysis tools for a wide biomedical and non-biomedical research community.
Journal ArticleDOI
An experimentally-supported genome-scale metabolic network reconstruction for Yersinia pestis CO92.
Pep Charusanti,Sadhana Chauhan,Kathleen McAteer,Joshua A. Lerman,Daniel R. Hyduke,Vladimir L. Motin,Charles Ansong,Joshua N. Adkins,Bernhard O. Palsson +8 more
TL;DR: The Y. pestis genome-scale metabolic reconstruction presented here, which has been benchmarked against experimental data and correctly reproduces known phenotypes, provides an in silico platform with which to investigate the metabolism of this important human pathogen.
References
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