Steady-state joint distribution for first-order stochastic reaction kinetics

Abstract

While the analytical solution for the marginal distribution of a stochastic chemical reaction network has been extensively studied, its joint distribution, i.e. the solution of a high-dimensional chemical master equation, has received much less attention. Here we develop a novel method of computing the exact joint distributions of a wide class of first-order stochastic reaction systems in steady-state conditions. The effectiveness of our method is validated by applying it to four gene expression models of biological significance, including models with 2A peptides, nascent mRNA, gene regulation, translational bursting, and alternative splicing.

arXiv comment33 pages, 6 figures

References in corpus (9)

• Emergence of scaling in random networks
• Multilayer Networks
• The structure and dynamics of multilayer networks
• The physics of spreading processes in multilayer networks
• The Multilayer Nature of Ecological Networks
• Emergence of network features from multiplexity
• Modeling the Multi-layer Nature of the European Air Transport Network: Resilience and Passengers Re-scheduling under random failures
• More is the Same; Phase Transitions and Mean Field Theories
• Spatial patterns emerging from a stochastic process near criticality