Independent, Incidence Independent and Weakly Reversible Decompositions of Chemical Reaction Networks

TL;DR

This paper investigates the structure of chemical reaction networks, focusing on independent and incidence independent decompositions, their relation to weak reversibility, and methods to identify such decompositions to better understand steady states.

Contribution

It introduces a method for finding incidence independent decompositions, expands their applicability to steady state components, and characterizes all such decompositions for CRNs.

Findings

All forms of independent and incidence independent decompositions are determined.

Incidence independence guarantees weak reversibility in certain subclasses.

A new method for identifying incidence independent decompositions is established.

Abstract

Chemical reaction networks (CRNs) are directed graphs with reactant or product complexes as vertices, and reactions as arcs. A CRN is weakly reversible if each of its connected components is strongly connected. Weakly reversible networks can be considered as the most important class of reaction networks. Now, the stoichiometric subspace of a network is the linear span of the reaction vectors (i.e., difference between the product and the reactant complexes). A decomposition of a CRN is independent (incidence independent) if the direct sum of the stoichiometric subspaces (incidence maps) of the subnetworks equals the stoichiometric subspace (incidence map) of the whole network. Decompositions can be used to study relationships between steady states of the whole system (induced from partitioning the reaction set of the underlying network) and those of its subsystems. In this work, we revisit our novel method of finding independent decomposition, and use it to expand applicability on (vector) components of steady states. We also explore CRNs with embedded deficiency zero independent subnetworks. In addition, we establish a method for finding incidence independent decomposition of a CRN. We determine all the forms of independent and incidence independent decompositions of a network, and provide the number of such decompositions. Lastly, for weakly reversible networks, we determine that incidence independence is a sufficient condition for weak reversibility of a decomposition, and we identify subclasses of weakly reversible networks where any independent decomposition is weakly reversible.