Opportunities at the interface of network science and metabolic modeling

Varshit Dusad, Denise Thiel, Mauricio Barahona, Hector C. Keun, Diego A. Oyarzún*

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

Abstract

Metabolism plays a central role in cell physiology because it provides the molecular machinery for growth. At the genome-scale, metabolism is made up of thousands of reactions interacting with one another. Untangling this complexity is key to understand how cells respond to genetic, environmental, or therapeutic perturbations. Here we discuss the roles of two complementary strategies for the analysis of genome-scale metabolic models: Flux Balance Analysis (FBA) and network science. While FBA estimates metabolic flux on the basis of an optimization principle, network approaches reveal emergent properties of the global metabolic connectivity. We highlight how the integration of both approaches promises to deliver insights on the structure and function of metabolic systems with wide-ranging implications in discovery science, precision medicine and industrial biotechnology.

Original languageEnglish
Article number591049
Number of pages9
JournalFrontiers in Bioengineering and Biotechnology
Volume8
DOIs
Publication statusPublished - 25 Jan 2021

Keywords

  • flux balance analysis
  • genome scale metabolic modeling
  • machine learning
  • network science
  • synthetic biology
  • systems biology

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