Identify structures underlying out-of-equilibrium reaction networks with random graph analysis.

ABSTRACT: Network measures have proven very successful in identifying structural patterns in complex systems (e.g., a living cell, a neural network, the Internet). How such measures can be applied to understand the rational and experimental design of chemical reaction networks (CRNs) is unknown. Here, we develop a procedure to model CRNs as a mathematical graph on which network measures and a random graph analysis can be applied. We used an enzymatic CRN (for which a mass-action model was previously developed) to show that the procedure provides insights into its network structure and properties. Temporal analyses, in particular, revealed when feedback interactions emerge in such a network, indicating that CRNs comprise various reactions that are being added and removed over time. We envision

SUBMITTER: da Cunha EF 

PROVIDER: S-EPMC11736930 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature