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Insights into Dynamic Network States Using Metabolomic Data

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High-Throughput Metabolomics

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1978))

Abstract

Metabolomic data is the youngest of the high-throughput data types; however, it is potentially one of the most informative, as it provides a direct, quantitative biochemical phenotype. There are a number of ways in which metabolomic data can be analyzed in systems biology; however, the thermodynamic and kinetic relevance of these data cannot be overstated. Genome-scale metabolic network reconstructions provide a natural context to incorporate metabolomic data in order to provide insight into the condition-specific kinetic characteristics of metabolic networks. Herein we discuss how metabolomic data can be incorporated into constraint-based models in a flexible framework that enables scaling from small pathways to cell-scale models, while being able to accommodate coarse-grained to more detailed, allosteric interactions, all using the well-known principle of mass action.

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Authors and Affiliations

  1. Center for Bioinformatics Tübingen (ZBIT), University of Tübingen, Tübingen, Germany

    Reihaneh Mostolizadeh & Andreas Dräger

  2. University of California, Los Angeles, Los Angeles, CA, USA

    Neema Jamshidi

  3. Department for Computer Science, University of Tübingen, Tübingen, Germany

    Reihaneh Mostolizadeh & Andreas Dräger

  4. German Center for Infection Research (DZIF), Tübingen, Germany

    Reihaneh Mostolizadeh & Andreas Dräger

Authors
  1. Reihaneh Mostolizadeh
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  2. Andreas Dräger
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  3. Neema Jamshidi
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Corresponding author

Correspondence to Neema Jamshidi .

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Editors and Affiliations

  1. Department of Biochemistry and Molecular Genetics, University of Colorado Denver, Aurora, CO, USA

    Angelo D'Alessandro

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Mostolizadeh, R., Dräger, A., Jamshidi, N. (2019). Insights into Dynamic Network States Using Metabolomic Data. In: D'Alessandro, A. (eds) High-Throughput Metabolomics. Methods in Molecular Biology, vol 1978. Humana, New York, NY. https://doi.org/10.1007/978-1-4939-9236-2_15

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  • DOI: https://doi.org/10.1007/978-1-4939-9236-2_15

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-4939-9235-5

  • Online ISBN: 978-1-4939-9236-2

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