MetaboTools: A comprehensive toolbox for analysis of genome-scale metabolic models
Abstract
Metabolomic data sets provide a direct read-out of cellular phenotypes and are increasingly generated to study biological questions. Previous work, by us and others, revealed the potential of analyzing extracellular metabolomic data in the context of the metabolic model using constraint-based modeling. With the MetaboTools, we make our methods available to the broader scientific community. The MetaboTools consist of a protocol, a toolbox, and tutorials of two use cases. The protocol describes, in a step-wise manner, the workflow of data integration, and computational analysis. The MetaboTools comprise the Matlab code required to complete the workflow described in the protocol. Tutorials explain the computational steps for integration of two different data sets and demonstrate a comprehensive set of methods for the computational analysis of metabolic models and stratification thereof into different phenotypes. The presented workflow supports integrative analysis of multiple omics data sets. Importantly, all analysis tools can be applied to metabolic models without performing the entire workflow. Taken together, the MetaboTools constitute a comprehensive guide to the intra-model analysis of extracellular metabolomic data from microbial, plant, or human cells. In conclusion, this computational modeling resource offers a broad set of computational analysis tools for a wide biomedical and non-biomedical researchmore »
- Authors:
-
- Univ. of Luxembourg, Esch-sur-Alzette (Luxembourg)
- Publication Date:
- Research Org.:
- Univ. of Luxembourg, Esch-sur-Alzette (Luxembourg)
- Sponsoring Org.:
- USDOE Office of Science (SC), Biological and Environmental Research (BER); European Union (EU)
- OSTI Identifier:
- 1326674
- Grant/Contract Number:
- SC0010429; 668738
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Frontiers in Physiology
- Additional Journal Information:
- Journal Volume: 7; Journal ID: ISSN 1664-042X
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 59 BASIC BIOLOGICAL SCIENCES; 97 MATHEMATICS AND COMPUTING; constraint-based reconstruction and analysis (COBRA); metabolomics; metabolism; metabolic modeling; metabolic phenotypes; protocol; modelanalysis
Citation Formats
Aurich, Maike K., Fleming, Ronan M. T., and Thiele, Ines. MetaboTools: A comprehensive toolbox for analysis of genome-scale metabolic models. United States: N. p., 2016.
Web. doi:10.3389/fphys.2016.00327.
Aurich, Maike K., Fleming, Ronan M. T., & Thiele, Ines. MetaboTools: A comprehensive toolbox for analysis of genome-scale metabolic models. United States. https://doi.org/10.3389/fphys.2016.00327
Aurich, Maike K., Fleming, Ronan M. T., and Thiele, Ines. Wed .
"MetaboTools: A comprehensive toolbox for analysis of genome-scale metabolic models". United States. https://doi.org/10.3389/fphys.2016.00327. https://www.osti.gov/servlets/purl/1326674.
@article{osti_1326674,
title = {MetaboTools: A comprehensive toolbox for analysis of genome-scale metabolic models},
author = {Aurich, Maike K. and Fleming, Ronan M. T. and Thiele, Ines},
abstractNote = {Metabolomic data sets provide a direct read-out of cellular phenotypes and are increasingly generated to study biological questions. Previous work, by us and others, revealed the potential of analyzing extracellular metabolomic data in the context of the metabolic model using constraint-based modeling. With the MetaboTools, we make our methods available to the broader scientific community. The MetaboTools consist of a protocol, a toolbox, and tutorials of two use cases. The protocol describes, in a step-wise manner, the workflow of data integration, and computational analysis. The MetaboTools comprise the Matlab code required to complete the workflow described in the protocol. Tutorials explain the computational steps for integration of two different data sets and demonstrate a comprehensive set of methods for the computational analysis of metabolic models and stratification thereof into different phenotypes. The presented workflow supports integrative analysis of multiple omics data sets. Importantly, all analysis tools can be applied to metabolic models without performing the entire workflow. Taken together, the MetaboTools constitute a comprehensive guide to the intra-model analysis of extracellular metabolomic data from microbial, plant, or human cells. In conclusion, this computational modeling resource offers a broad set of computational analysis tools for a wide biomedical and non-biomedical research community.},
doi = {10.3389/fphys.2016.00327},
journal = {Frontiers in Physiology},
number = ,
volume = 7,
place = {United States},
year = {Wed Aug 03 00:00:00 EDT 2016},
month = {Wed Aug 03 00:00:00 EDT 2016}
}
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Contextualization Procedure and Modeling of Monocyte Specific TLR Signaling
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Global Profiling of Metabolic Adaptation to Hypoxic Stress in Human Glioblastoma Cells
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