Literature DB >> 22144170

Spatial and stochastic cellular modeling with the Smoldyn simulator.

Steven S Andrews1.   

Abstract

This chapter describes how to use Smoldyn, which is a computer program for modeling cellular systems with spatial and stochastic detail. Smoldyn represents each molecule of interest as an individual point-like particle. These simulated molecules diffuse, interact with surfaces (e.g., biological membranes), and undergo chemical reactions much as they would in real biochemical systems. Smoldyn has been used to model signal transduction within bacterial cells, pheromone signaling between yeast cells, bacterial carboxysome function, diffusion in crowded spaces, and many other systems. A new "rule-based modeling" feature automatically generates chemical species and reactions as they arise in simulations due to protein modifications and complexation. Smoldyn is easy to use, quantitatively accurate, and computationally efficient. It is generally best for systems with length scales between nanometers and several microns, time scales from tens of nanoseconds to tens of minutes, and up to about 10(5) individual molecules. Smoldyn runs on Macintosh, Linux, or Windows systems, is open source, and can be downloaded from http://www.smoldyn.org.

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Year:  2012        PMID: 22144170     DOI: 10.1007/978-1-61779-361-5_26

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  17 in total

1.  Discrete-continuous reaction-diffusion model with mobile point-like sources and sinks.

Authors:  Svyatoslav Kondrat; Olav Zimmermann; Wolfgang Wiechert; Eric von Lieres
Journal:  Eur Phys J E Soft Matter       Date:  2016-01-29       Impact factor: 1.890

2.  Efficient stochastic simulation of chemical kinetics networks using a weighted ensemble of trajectories.

Authors:  Rory M Donovan; Andrew J Sedgewick; James R Faeder; Daniel M Zuckerman
Journal:  J Chem Phys       Date:  2013-09-21       Impact factor: 3.488

Review 3.  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 4.  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

5.  Biocellion: accelerating computer simulation of multicellular biological system models.

Authors:  Seunghwa Kang; Simon Kahan; Jason McDermott; Nicholas Flann; Ilya Shmulevich
Journal:  Bioinformatics       Date:  2014-07-26       Impact factor: 6.937

6.  Detailed simulations of cell biology with Smoldyn 2.1.

Authors:  Steven S Andrews; Nathan J Addy; Roger Brent; Adam P Arkin
Journal:  PLoS Comput Biol       Date:  2010-03-12       Impact factor: 4.475

Review 7.  Modeling cellular compartmentation in one-carbon metabolism.

Authors:  Marco Scotti; Lorenzo Stella; Emily J Shearer; Patrick J Stover
Journal:  Wiley Interdiscip Rev Syst Biol Med       Date:  2013-02-13

8.  Modeling and simulation of biological systems from image data.

Authors:  Ivo F Sbalzarini
Journal:  Bioessays       Date:  2013-03-27       Impact factor: 4.345

9.  The autoregulation of a eukaryotic DNA transposon.

Authors:  Corentin Claeys Bouuaert; Karen Lipkow; Steven S Andrews; Danxu Liu; Ronald Chalmers
Journal:  Elife       Date:  2013-06-18       Impact factor: 8.140

10.  Multiscale reaction-diffusion simulations with Smoldyn.

Authors:  Martin Robinson; Steven S Andrews; Radek Erban
Journal:  Bioinformatics       Date:  2015-03-18       Impact factor: 6.937

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