Opportunities at the Interface of Network Science and Metabolic Modeling

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.

Automated summary

Metabolism is crucial for cell growth, composed of thousands of reactions at the genome-scale. Flux Balance Analysis and network science are two complementary strategies for analyzing genome-scale metabolic models, offering insights into the structure and function of metabolic systems. Integration of both approaches can deliver comprehensive understanding with implications in discovery science, precision medicine, and industrial biotechnology.