Abstract

Characterising biochemical reaction network structure in mathematical terms enables the inference of functional biochemical consequences from network structure with existing mathematical techniques and spurs the development of new mathematics that exploits the peculiarities of biochemical network structure. The structure of a biochemical network may be specified by reaction stoichiometry, that is, the relative quantities of each molecule produced and consumed in each reaction of the network. A biochemical network may also be specified at a higher level of resolution in terms of the internal structure of each molecule and how molecular structures are transformed by each reaction in a network. The stoichiometry for a set of reactions can be compiled into a stoichiometric matrix N∈Zm×n, where each row corresponds to a molecule and each column corresponds to a reaction. We demonstrate that a stoichiometric matrix may be split into the sum of m−rank(N) moiety transition matrices, each of which corresponds to a subnetwork accessible to a structurally identifiable conserved moiety. The existence of this moiety matrix splitting is a property that distinguishes a stoichiometric matrix from an arbitrary rectangular matrix.

Highlights

  • Understanding biochemical networks is of great practical importance in systems biology

  • A key output of this reconstruction process is a stoichiometric matrix, where every row corresponds to a molecule, every column corresponds to a reaction, and each entry corresponds to the relative quantity of a molecule produced or consumed in a reac

  • A biochemical network with m molecules and n reactions may be expressed as a hypergraph H(V, Y ) that consists of a set of m vertices V := {V1, . . . , Vm}, each corresponding to one molecule, and a set of n hyperedges Y := {Y1, . . . , Yn}, each corresponding to one reaction

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Summary

Introduction

Understanding biochemical networks is of great practical importance in systems biology. A variety of approaches for mathematical modelling of reaction networks have been developed, including topological (Barabási and Oltvai, 2004), stochastic, deterministic (Ingalls, 2013) and constraint-based modelling (Palsson, 2015). Before any biological application of any of these modelling approaches, an abstract representation of the relative quantities of molecules produced and consumed in each reaction of a reaction network is reconstructed from experimental literature. A key output of this reconstruction process is a stoichiometric matrix, where every row corresponds to a molecule, every column corresponds to a reaction, and each entry corresponds to the relative quantity of a molecule produced or consumed in a reac-. A stoichiometric matrix is the central mathematical object in any model of a reaction network for many biological, biotechnological and biomedical research applications. Characterising the mathematical properties of stoichiometric matrices is a fundamental problem in mathematical biology

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