ArticleJournal of mathematical biology2018
General solution of the chemical master equation and modality of marginal distributions for hierarchic first-order reaction networks.
Article in Journal of mathematical biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Control of COVID-19 Outbreaks under Stochastic Community Dynamics, Bimodality, or Limited Vaccination.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2022Article
- Solving the chemical master equation for monomolecular reaction systems and beyond: a Doi-Peliti path integral view.Journal of mathematical biology · 2021Article
- Comprehensive Review of Models and Methods for Inferences in Bio-Chemical Reaction Networks.Frontiers in genetics · 2019Review
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3 authors.
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Abstract
Multimodality is a phenomenon which complicates the analysis of statistical data based exclusively on mean and variance. Here, we present criteria for multimodality in hierarchic first-order reaction networks, consisting of catalytic and splitting reactions. Those networks are characterized by independent and dependent subnetworks. First, we prove the general solvability of the Chemical Master Equation (CME) for this type of reaction network and thereby extend the class of solvable CME's. Our general solution is analytical in the sense that it allows for a detailed analysis of its statistical properties. Given Poisson/deterministic initial conditions, we then prove the independent species to be Poisson/binomially distributed, while the dependent species exhibit generalized Poisson/Khatri Type B distributions. Generalized Poisson/Khatri Type B distributions are multimodal for an appropriate choice of parameters. We illustrate our criteria for multimodality by several basic models, as well as the well-known two-stage transcription-translation network and Bateman's model from nuclear physics. For both examples, multimodality was previously not reported.
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