title: Uncoupled analysis of stochastic reaction networks in fluctuating environments.
abstract: The dynamics of stochastic reaction networks within cells are inevitably modulated by factors considered extrinsic to the network such as, for instance, the fluctuations in ribosome copy numbers for a gene regulatory network. While several recent studies demonstrate the importance of accounting for such extrinsic components, the resulting models are typically hard to analyze. In this work we develop a general mathematical framework that allows to uncouple the network from its dynamic environment by incorporating only the environment's effect onto the network into a new model. More technically, we show how such fluctuating extrinsic components (e.g., chemical species) can be marginalized in order to obtain this decoupled model. We derive its corresponding process- and master equations and show how stochastic simulations can be performed. Using several case studies, we demonstrate the significance of the approach.
authors.affiliation: Department of Information Technology and Electrical Engineering, ETH Zurich, Zurich, Switzerland.
authors.forename: Christoph
authors.initials: C
authors.lastname: Zechner
authors.affiliation: Department of Electrical Engineering and Information Technology, Technische Universität Darmstadt, Darmstadt, Germany.
authors.forename: Heinz
authors.initials: H
authors.lastname: Koeppl
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D053263:Gene Regulatory Networks / Q000235:genetics; D008954:Models, Biological; D012270:Ribosomes / Q000235:genetics / Q000378:metabolism; D013269:Stochastic Processes