Unbiased Estimation of Parameter Sensitivities for Stochastic Chemical Reaction Networks

DOI10.1137/120898747zbMath1402.62190arXiv1210.3475OpenAlexW2963502558MaRDI QIDQ5404606

Ankit Gupta, Mustafa H. Khammash

Publication date: 28 March 2014

Published in: SIAM Journal on Scientific Computing (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1210.3475

zbMATH Keywords

Markov processcouplingrandom time changechemical reaction networkparameter sensitivityGillespieGirsanov

Mathematics Subject Classification ID

Markov processes: estimation; hidden Markov models (62M05) Monte Carlo methods (65C05) Computational methods for stochastic equations (aspects of stochastic analysis) (60H35) Chemistry (general) in thermodynamics and heat transfer (80A50) Systems biology, networks (92C42)

Related Items (8)

Convergence of Regularized Particle Filters for Stochastic Reaction Networks ⋮ Efficiency of the Girsanov Transformation Approach for Parametric Sensitivity Analysis of Stochastic Chemical Kinetics ⋮ On the validity of the Girsanov transformation method for sensitivity analysis of stochastic chemical reaction networks ⋮ Reduction for Stochastic Biochemical Reaction Networks with Multiscale Conservations ⋮ Variance of Finite Difference Methods for Reaction Networks with Non-Lipschitz Rate Functions ⋮ Estimation of Parameter Sensitivities for Stochastic Reaction Networks Using Tau-Leap Simulations ⋮ Low variance couplings for stochastic models of intracellular processes with time-dependent rate functions ⋮ Sensitivity analysis for multiscale stochastic reaction networks using hybrid approximations

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