Chemical reaction network decomposition technique for stability analysis. (December 2022)

• Record Type: Journal Article
• Authors: Lu, Yafei; Gao, Chuanhou; Dochain, Denis
• Is Part Of: Automatica. Volume 146(2022)
• Publication Date: 2022-12
• Subjects: Chemical reaction networks -- Stability -- Mass-action system -- Lyapunov function -- Decomposition; Automatic control -- Periodicals; Automation -- Periodicals; 629.805
• DOI: 10.1016/j.automatica.2022.110650
• Languages: English
• ISSNs: 0005-1098

Abstract

Abstract: This paper develops the concept of decomposition for chemical reaction networks, based on which a network decomposition technique is proposed to capture the stability of large-scale networks characterized by a high number of species, high dimension, high deficiency, and/or non-weakly reversible structure. We present some sufficient conditions to capture the stability of a network when it can be decomposed into a complex balanced subnetwork and a few 1-dimensional subnetworks (and/or a few two-species subnetworks) with shared species between different subnetworks. The results cover encouraging applications on autocatalytic networks with some frequently-encountered biochemical reactions examples of interest, such as the autophosphorylation of PAK1 and Aurora B kinase, or autocatalytic cycles originating from metabolism.