Moment-Based Methods for Parameter Inference and Experiment Design for Stochastic Biochemical Reaction Networks

DOI10.1145/2688906zbMath1373.92051OpenAlexW1997377511MaRDI QIDQ5270730

John Lygeros, Jakob Ruess

Publication date: 30 June 2017

Published in: ACM Transactions on Modeling and Computer Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1145/2688906

zbMATH Keywords

Fisher informationcontinuous-time Markov chainsmoment equationsparameter inferenceexperiment design

Mathematics Subject Classification ID

Biochemistry, molecular biology (92C40) Applications of continuous-time Markov processes on discrete state spaces (60J28)

Related Items (2)

Rapid Bayesian Inference for Expensive Stochastic Models ⋮ Parameter estimation for biochemical reaction networks using Wasserstein distances

Uses Software

• SUNDIALS
• StochDynTools
• CERENA

Cites Work

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• SUNDIALS
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• Computing the moments of high dimensional solutions of the master equation
• Qualitative and quantitative experiment design for phenomenological models - a survey
• Robust experiment design via stochastic approximation
• A multiple time interval finite state projection algorithm for the solution to the chemical master equation
• Parameter estimation for stochastic hybrid models of biochemical reaction networks
• Approximate Moment Dynamics for Chemically Reacting Systems

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