Literature DB >> 23656106

Perspective: Stochastic algorithms for chemical kinetics.

Daniel T Gillespie1, Andreas Hellander, Linda R Petzold.   

Abstract

We outline our perspective on stochastic chemical kinetics, paying particular attention to numerical simulation algorithms. We first focus on dilute, well-mixed systems, whose description using ordinary differential equations has served as the basis for traditional chemical kinetics for the past 150 years. For such systems, we review the physical and mathematical rationale for a discrete-stochastic approach, and for the approximations that need to be made in order to regain the traditional continuous-deterministic description. We next take note of some of the more promising strategies for dealing stochastically with stiff systems, rare events, and sensitivity analysis. Finally, we review some recent efforts to adapt and extend the discrete-stochastic approach to systems that are not well-mixed. In that currently developing area, we focus mainly on the strategy of subdividing the system into well-mixed subvolumes, and then simulating diffusional transfers of reactant molecules between adjacent subvolumes together with chemical reactions inside the subvolumes.

Mesh:

Year:  2013        PMID: 23656106      PMCID: PMC3656953          DOI: 10.1063/1.4801941

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


  51 in total

1.  Reaction-diffusion master equation in the microscopic limit.

Authors:  Stefan Hellander; Andreas Hellander; Linda Petzold
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2012-04-03

2.  Reaction-diffusion master equation, diffusion-limited reactions, and singular potentials.

Authors:  Samuel A Isaacson; David Isaacson
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2009-12-07

3.  Efficient formulations for exact stochastic simulation of chemical systems.

Authors:  Sean Mauch; Mark Stalzer
Journal:  IEEE/ACM Trans Comput Biol Bioinform       Date:  2011 Jan-Mar       Impact factor: 3.710

4.  Effect of reactant size on discrete stochastic chemical kinetics.

Authors:  Dan T Gillespie; Sotiria Lampoudi; Linda R Petzold
Journal:  J Chem Phys       Date:  2007-01-21       Impact factor: 3.488

5.  Effect of excluded volume on 2D discrete stochastic chemical kinetics.

Authors:  Sotiria Lampoudi; Dan T Gillespie; Linda R Petzold
Journal:  J Comput Phys       Date:  2009       Impact factor: 3.553

6.  Deterministic limit of stochastic chemical kinetics.

Authors:  Daniel T Gillespie
Journal:  J Phys Chem B       Date:  2009-02-12       Impact factor: 2.991

7.  Stochastic modelling of reaction-diffusion processes: algorithms for bimolecular reactions.

Authors:  Radek Erban; S Jonathan Chapman
Journal:  Phys Biol       Date:  2009-08-21       Impact factor: 2.583

8.  A diffusional bimolecular propensity function.

Authors:  Daniel T Gillespie
Journal:  J Chem Phys       Date:  2009-10-28       Impact factor: 3.488

9.  Automated estimation of rare event probabilities in biochemical systems.

Authors:  Bernie J Daigle; Min K Roh; Dan T Gillespie; Linda R Petzold
Journal:  J Chem Phys       Date:  2011-01-28       Impact factor: 3.488

10.  Spatio-temporal correlations can drastically change the response of a MAPK pathway.

Authors:  Koichi Takahashi; Sorin Tanase-Nicola; Pieter Rein ten Wolde
Journal:  Proc Natl Acad Sci U S A       Date:  2010-01-25       Impact factor: 11.205

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  53 in total

1.  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

2.  BioSimulator.jl: Stochastic simulation in Julia.

Authors:  Alfonso Landeros; Timothy Stutz; Kevin L Keys; Alexander Alekseyenko; Janet S Sinsheimer; Kenneth Lange; Mary E Sehl
Journal:  Comput Methods Programs Biomed       Date:  2018-10-10       Impact factor: 5.428

3.  Noise-induced regime shifts: A quantitative characterization.

Authors:  Sayantari Ghosh; Amit Kumar Pal; Indrani Bose
Journal:  Eur Phys J E Soft Matter       Date:  2013-10-28       Impact factor: 1.890

4.  ANALYSIS AND DESIGN OF JUMP COEFFICIENTS IN DISCRETE STOCHASTIC DIFFUSION MODELS.

Authors:  Lina Meinecke; Stefan Engblom; Andreas Hellander; Per Lötstedt
Journal:  SIAM J Sci Comput       Date:  2016-01-06       Impact factor: 2.373

5.  MOLNs: A CLOUD PLATFORM FOR INTERACTIVE, REPRODUCIBLE, AND SCALABLE SPATIAL STOCHASTIC COMPUTATIONAL EXPERIMENTS IN SYSTEMS BIOLOGY USING PyURDME.

Authors:  Brian Drawert; Michael Trogdon; Salman Toor; Linda Petzold; Andreas Hellander
Journal:  SIAM J Sci Comput       Date:  2016-06-01       Impact factor: 2.373

Review 6.  Modeling for (physical) biologists: an introduction to the rule-based approach.

Authors:  Lily A Chylek; Leonard A Harris; James R Faeder; William S Hlavacek
Journal:  Phys Biol       Date:  2015-07-16       Impact factor: 2.583

Review 7.  Rule-based modeling: a computational approach for studying biomolecular site dynamics in cell signaling systems.

Authors:  Lily A Chylek; Leonard A Harris; Chang-Shung Tung; James R Faeder; Carlos F Lopez; William S Hlavacek
Journal:  Wiley Interdiscip Rev Syst Biol Med       Date:  2013-09-30

8.  The pseudo-compartment method for coupling partial differential equation and compartment-based models of diffusion.

Authors:  Christian A Yates; Mark B Flegg
Journal:  J R Soc Interface       Date:  2015-05-06       Impact factor: 4.118

9.  How spatial heterogeneity shapes multiscale biochemical reaction network dynamics.

Authors:  Peter Pfaffelhuber; Lea Popovic
Journal:  J R Soc Interface       Date:  2015-03-06       Impact factor: 4.118

10.  Reaction rates for mesoscopic reaction-diffusion kinetics.

Authors:  Stefan Hellander; Andreas Hellander; Linda Petzold
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2015-02-23
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