Analytical singular value decomposition for a class of stoichiometry matrices

TL;DR

This paper derives analytical singular value decompositions for stoichiometry matrices in reaction-diffusion systems, enabling better understanding of complex biochemical networks with spatial compartments.

Contribution

It introduces a novel analytical approach to SVD of stoichiometry matrices for reaction-diffusion systems using Kronecker product formulations, applicable across different reaction and diffusion regimes.

Findings

Exact SVD derived for homogeneous systems across all scales.

Approximate SVD obtained for heterogeneous boundary reactions with fast diffusion.

SVD expressed as Kronecker products of smaller matrices.

Abstract

We present the analytical singular value decomposition of the stoichiometry matrix for a spatially discrete reaction-diffusion system on a one dimensional domain. The domain has two subregions which share a single common boundary. Each of the subregions is further partitioned into a finite number of compartments. Chemical reactions can occur within a compartment, whereas diffusion is represented as movement between adjacent compartments. Inspired by biology, we study both 1) the case where the reactions on each side of the boundary are different and only certain species diffuse across the boundary as well as 2) the case with spatially homogenous reactions and diffusion. We write the stoichiometry matrix for these two classes of systems using a Kronecker product formulation. For the first scenario, we apply linear perturbation theory to derive an approximate singular value decomposition in the limit as diffusion becomes much faster than reactions. For the second scenario, we derive an exact analytical singular value decomposition for all relative diffusion and reaction time scales. By writing the stoichiometry matrix using Kronecker products, we show that the singular vectors and values can also be written concisely using Kronecker products. Ultimately, we find that the singular value decomposition of the reaction-diffusion stoichiometry matrix depends on the singular value decompositions of smaller matrices. These smaller matrices represent modified versions of the reaction-only stoichiometry matrices and the analytically known diffusion-only stoichiometry matrix. Our results provide a mathematical framework that can be used to study complex biochemical systems with metabolic compartments. MATLAB code for calculating the SVD equations is available at \url{www.github.com/MathBioCU/ReacDiffStoicSVD}.