Network Combination to Persistence of High-dimensional Delayed Complex Balanced Mass-action Systems
Xiaoyu Zhang, Chunhou Gao, Denis Dochain

TL;DR
This paper introduces a novel combination approach for analyzing the persistence of high-dimensional delayed complex balanced mass-action systems, expanding understanding of their long-term behavior.
Contribution
It proposes inheritable combination methods based on semilocking sets to derive sufficient conditions for persistence in high-dimensional delayed systems.
Findings
Derived new sufficient conditions for persistence.
Expanded classes of delayed chemical reaction networks with proven persistence.
Validated approach through practical examples.
Abstract
Complex balanced mass-action systems (CBMASs) are of great importance in the filed of biochemical reaction networks. However analyzing the persistence of these networks with high dimensions and time delays poses significant challenges. To tackle this, we propose a novel approach that combines 1-dimensional (1d) or 2d delayed CBMASs (DeCBMASs) and introduces inheritable combination methods based on the relationship between semilocking sets and intersecting species. These methods account for various scenarios, including cases where the set of intersecting species is empty, or there are no common species in non-trivial semilocking sets and the intersecting species set, or when special forms are present. By utilizing these combination methods, we derive sufficient conditions for the persistence of high-dimensional DeCBMASs. This significantly expands the known class of delayed chemical…
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Taxonomy
TopicsGene Regulatory Network Analysis · Microbial Metabolic Engineering and Bioproduction · Computational Drug Discovery Methods
