Insights into Dynamic Network States Using Metabolomic Data

Methods Mol Biol. 2019;1978:243-258. doi: 10.1007/978-1-4939-9236-2_15.


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.

Keywords: Dynamic network states; Metabolomics; Systems biology.

MeSH terms

  • Genome
  • Metabolic Networks and Pathways / genetics*
  • Metabolomics / methods*
  • Systems Biology / methods*