Sensitivity analysis for multiscale stochastic reaction networks using hybrid approximations

DOI10.1007/s11538-018-0521-4zbMath1422.92054arXiv1801.04708OpenAlexW2964349235WikidataQ57287690 ScholiaQ57287690MaRDI QIDQ2325578

Ankit Gupta, Mustafa H. Khammash

Publication date: 26 September 2019

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

Full work available at URL: https://arxiv.org/abs/1801.04708

zbMATH Keywords

reduced modelscouplingpiecewise deterministic Markov processesparameter sensitivitystochastic reaction networksmultiscale networksrandom time change representation

Mathematics Subject Classification ID

Computational methods in Markov chains (60J22) PDEs in connection with biology, chemistry and other natural sciences (35Q92) Kinetics in biochemical problems (pharmacokinetics, enzyme kinetics, etc.) (92C45) Biochemistry, molecular biology (92C40) Numerical analysis or methods applied to Markov chains (65C40) Computational methods for stochastic equations (aspects of stochastic analysis) (60H35) Systems biology, networks (92C42)

Related Items (4)

Convergence of Regularized Particle Filters for Stochastic Reaction Networks ⋮ Parameter sensitivity analysis for biochemical reaction networks ⋮ Stochastic filtering for multiscale stochastic reaction networks based on hybrid approximations ⋮ Stochastic simulation of biochemical systems: in memory of Dan T. Gillespie's contributions

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