Tag: Stochastic Simulation

Dizzy 1.11.4 – Chemical Kinetics Stochastic Simulation

Dizzy 1.11.4

:: DESCRIPTION

Dizzy is a chemical kinetics stochastic simulation software package written in Java. It provides a model definition environment and an implementation of the Gillespie, Gibson-Bruck, and Tau-Leap stochastic algorithms. Dizzy is capable of importing and exporting the SBML model definition language, as well as displaying models graphically using the Cytoscape software system.

::DEVELOPER

Dizzy team

:: SCREENSHOTS

:: REQUIREMENTS

  • Windows/ Linux
  • JAVA

:: DOWNLOAD

Dizzy

:: MORE INFORMATION

Citation:

Ramsey S, Orrell D, Bolouri H. , “Dizzy: stochastic simulation of large-scale genetic regulatory networks.”
J Bioinform Comput Biol. 2005 Apr;3(2):415-36.

FERN 1.4 – Stochastic Simulation & Evaluation of Reaction Networks

FERN 1.4

:: DESCRIPTION

FERN (Framework for Evaluation of Reaction Networks) is an extensible and comprehensive framework for efficient simulations and analysis of chemical reaction networks written in Java. It includes state of the art algorithms for stochastic simulation and a powerful visualization system based on gnuplot and Cytoscape.FERN is subdivided into three layers for network representation, simulation and visualization of the simulation results each of which can be easily extended. It provides efficient and accurate state-of-the-art stochastic simulation algorithms for well-mixed chemical systems and a powerful observer system, which makes it possible to track and control the simulation progress on every level.

::DEVELOPER

Institut für Informatik, Ludwig-Maximilians-Universität München

:: SCREENSHOTS

:: REQUIREMENTS

:: DOWNLOAD

FERN

:: MORE INFORMATION

Citation

Florian Erhard, Caroline C. Friedel, Ralf Zimmer.
FERN – a Java framework for stochastic simulation and evaluation of reaction networks.
BMC Bioinformatics, vol 9, no. 1, pp. 356, 2008.

SSC 0.6 – Stochastic Simulation Compiler

SSC 0.6

:: DESCRIPTION

SSC (Stochastic Simulation Compiler) is a tool for creating exact stochastic simulations of biochemical reaction networks. The models are written in a succinct, intuitive format, where reactions are specified with patterns. Patterns mention only the part of the compound relevant to a given reaction, and correspond to an intuitive view of biochemical reactions. This enables complex biochemical signaling networks to be specified without the knowledge of any formal programming languages.

::DEVELOPER

Lis, Mieszko; Artyomov, Maxim N.; Chakraborty, Arup K.; Devadas, Srinivas @ MIT

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

SSC

:: MORE INFORMATION

Citation:

Lis, Mieszko et al. “Efficient stochastic simulation of reaction–diffusion processes via direct compilation.” Bioinformatics 25.17 (2009): 2289 -2291.