Time-dependent propagators for stochastic models of gene expression: an analytical method

DOI10.1007/s00285-017-1196-4zbMath1426.35217OpenAlexW2774001441WikidataQ46238559 ScholiaQ46238559MaRDI QIDQ1659718

Carsten Marr, Nikola Popović, Frits Veerman

Publication date: 22 August 2018

Published in: Journal of Mathematical Biology (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00285-017-1196-4

zbMATH Keywords

perturbation techniquesprobability generating functiondynamical systemsasymptotic analysispropagatorstochastic gene expression

Mathematics Subject Classification ID

Continuous-time Markov processes on general state spaces (60J25) Dynamical systems in biology (37N25) PDEs in connection with biology, chemistry and other natural sciences (35Q92) Biochemistry, molecular biology (92C40) Asymptotic expansions of solutions to PDEs (35C20) Ordinary differential equations and systems with randomness (34F05) Numerical aspects of the method of characteristics for initial value and initial-boundary value problems involving PDEs (65M25) Genetics and epigenetics (92D10) Asymptotic expansions of solutions to ordinary differential equations (34E05) First-order hyperbolic equations (35L02) Initial value problems for systems of linear first-order PDEs (35F40)

Related Items

Modulation of nuclear and cytoplasmic mRNA fluctuations by time-dependent stimuli: analytical distributions ⋮ Parameter inference with analytical propagators for stochastic models of autoregulated gene expression ⋮ Statistics of nascent and mature RNA fluctuations in a stochastic model of transcriptional initiation, elongation, pausing, and termination ⋮ Development of a fractional Wiener-Hermite expansion for analyzing the fractional stochastic models ⋮ Dimensionality reduction via path integration for computing mRNA distributions ⋮ Path integral approach to generating functions for multistep post-transcription and post-translation processes and arbitrary initial conditions ⋮ Mixture distributions in a stochastic gene expression model with delayed feedback: a WKB approximation approach

Uses Software

• DLMF

Cites Work

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