Literature DB >> 18067349

A modified next reaction method for simulating chemical systems with time dependent propensities and delays.

David F Anderson1.   

Abstract

Chemical reaction systems with a low to moderate number of molecules are typically modeled as discrete jump Markov processes. These systems are oftentimes simulated with methods that produce statistically exact sample paths such as the Gillespie algorithm or the next reaction method. In this paper we make explicit use of the fact that the initiation times of the reactions can be represented as the firing times of independent, unit rate Poisson processes with internal times given by integrated propensity functions. Using this representation we derive a modified next reaction method and, in a way that achieves efficiency over existing approaches for exact simulation, extend it to systems with time dependent propensities as well as to systems with delays.

Year:  2007        PMID: 18067349     DOI: 10.1063/1.2799998

Source DB:  PubMed          Journal:  J Chem Phys        ISSN: 0021-9606            Impact factor:   3.488


  57 in total

1.  Modelling the long-term dynamics of pre-vaccination pertussis.

Authors:  Ganna Rozhnova; Ana Nunes
Journal:  J R Soc Interface       Date:  2012-06-20       Impact factor: 4.118

2.  Stochasticity in staged models of epidemics: quantifying the dynamics of whooping cough.

Authors:  Andrew J Black; Alan J McKane
Journal:  J R Soc Interface       Date:  2010-02-17       Impact factor: 4.118

3.  Constant-complexity stochastic simulation algorithm with optimal binning.

Authors:  Kevin R Sanft; Hans G Othmer
Journal:  J Chem Phys       Date:  2015-08-21       Impact factor: 3.488

4.  Fine-tuning anti-tumor immunotherapies via stochastic simulations.

Authors:  Giulio Caravagna; Roberto Barbuti; Alberto d'Onofrio
Journal:  BMC Bioinformatics       Date:  2012-03-28       Impact factor: 3.169

5.  Efficient computation of parameter sensitivities of discrete stochastic chemical reaction networks.

Authors:  Muruhan Rathinam; Patrick W Sheppard; Mustafa Khammash
Journal:  J Chem Phys       Date:  2010-01-21       Impact factor: 3.488

6.  Accurate stochastic simulation via the step anticipation tau-leaping (SAL) algorithm.

Authors:  Mary Sehl; Alexander V Alekseyenko; Kenneth L Lange
Journal:  J Comput Biol       Date:  2009-09       Impact factor: 1.479

7.  Stochastic representations of ion channel kinetics and exact stochastic simulation of neuronal dynamics.

Authors:  David F Anderson; Bard Ermentrout; Peter J Thomas
Journal:  J Comput Neurosci       Date:  2014-11-19       Impact factor: 1.621

8.  Inferring single-cell gene expression mechanisms using stochastic simulation.

Authors:  Bernie J Daigle; Mohammad Soltani; Linda R Petzold; Abhyudai Singh
Journal:  Bioinformatics       Date:  2015-01-07       Impact factor: 6.937

9.  Lazy Updating of hubs can enable more realistic models by speeding up stochastic simulations.

Authors:  Kurt Ehlert; Laurence Loewe
Journal:  J Chem Phys       Date:  2014-11-28       Impact factor: 3.488

10.  Probability distributed time delays: integrating spatial effects into temporal models.

Authors:  Tatiana T Marquez-Lago; André Leier; Kevin Burrage
Journal:  BMC Syst Biol       Date:  2010-03-04
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.