BioNetS - UNC Chapel Hill

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BioNetS

BioNetS

Biochemical Network Stochastic Simulator

An easy to use and blazingly fast stochastic ODE solver, using Gillespie, chemical Langevin, and any hybrid of the two.

 

 

Introduction

We have developed the software package Biochemical Network Stochastic Simulator (BioNetS) for efficiently and accurately simulating stochastic models of biochemical networks.  BioNetS has a graphical user interface that allows models to be entered in a straightforward manner, and allows the user to specify the type of random variable (discrete or continuous) for each chemical species in the network.  The discrete variables are simulated using an optimized implementation of the Gillespie algorithm. For the continuous random variables, BioNetS constructs and numerically solves the appropriate chemical Langevin equations.  The software package has been designed to scale efficiently with network size, thereby allowing large systems to be studied.

Further Details

BioNetS is a code generator. As input, you enter in the reactions using a standard spreadsheet like interface, or import them from an SBML file. Then you set which type of solver you want and which optional statistics should be accumulated during the run. You can then run the simulation from within BioNetS, export the executable for use from Matlab or DataTank or the unix shel. You can even view the C++ source code that gets generated and incorporate it into your own program.

Because the code is generated for each reaction system, and with the exact reactions statistics you want to compute, it is possible to tailor the code to the specific system. This allows code optimizations that a general purpose solver would not be able to do, and runs much faster. On a recent computer the Gillespie solver takes around five million steps per second and can use every gillespie step to accumulate histograms.

BioNetS on the Mac generates graphics that can be copied as pdf documents and pasted into presentations and publications.

Future

We want BioNetS to be a useful tool for working biologists as well as modellers.  If you encounter problems, if you have questions, or if there are capabilities you wish the software had, please contact us.

Authors David Adalsteinsson, Department of Mathematics, University of North Carolina at Chapel Hill.

Timothy Elston, Department of Pharmacology, University of North Carolina at Chapel Hill.

David McMillen, Department of Chemical and Physical Sciences, University of Toronto at Mississauga, Ontario L5L 1C6 Canada

Paper BioNetS is described in a paper that appeared in BMC Bioinformatics

Mac OS X Download disk image
Need the developer tools from Apple. These are free, come with all new macs and can be downloaded from Apple.

Java A Java version has been created by Todd Riley.
Go to the download page.

Dashboard Module DataTank works as a BioSpice agent, taking SBML as input and returning a time series. download.

 

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