A framework for deriving analytic steady states of biochemical reaction networks.

ABSTRACT: The long-term behaviors of biochemical systems are often described by their steady states. Deriving these states directly for complex networks arising from real-world applications, however, is often challenging. Recent work has consequently focused on network-based approaches. Specifically, biochemical reaction networks are transformed into weakly reversible and deficiency zero generalized networks, which allows the derivation of their analytic steady states. Identifying this transformation, however, can be challenging for large and complex networks. In this paper, we address this difficulty by breaking the complex network into smaller independent subnetworks and then transforming the subnetworks to derive the analytic steady states of each subnetwork. We show that stitching these solution

SUBMITTER: Hernandez BS 

PROVIDER: S-EPMC10129002 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature