sbioPN: sbioPN: Simulation of deterministic and stochastic spatial biochemical reaction networks using Petri Nets

sbioPN is a package suited to perform simulation of deterministic and stochastic systems of biochemical reaction networks with spatial effects. Models are defined using a subset of Petri Nets, in a way that is close at how chemical reactions are defined. For deterministic solutions, sbioPN creates the associated system of differential equations "on the fly", and solves it with a Runge Kutta Dormand Prince 45 explicit algorithm. For stochastic solutions, sbioPN offers two variants of Gillespie algorithm, or SSA. For hybrid deterministic/stochastic, it employs the Haseltine and Rawlings algorithm, that partitions the system in fast and slow reactions. sbioPN algorithms are developed in C to achieve adequate performance.

Install the latest version of this package by entering the following in R:
install.packages("sbioPN")
AuthorRoberto Bertolusso and Marek Kimmel
Date of publication2014-03-15 18:37:54
MaintainerRoberto Bertolusso <rbertolusso@rice.edu>
LicenseGPL (>= 2)
Version1.1.0

View on CRAN

Files

COPYING
inst
inst/COPYRIGHTS
src
src/sGillespieDirectCR.c
src/helper.h
src/helper.c
src/sHaseltineRawlings.c
src/sGillespieOptimDirect.c
src/quicksort.c
src/quicksort.h
NAMESPACE
R
R/sRungeKuttaDormandPrince45.R R/sGillespieDirectCR.R R/sHaseltineRawlings.R R/helper.R R/sGillespieOptimDirect.R
MD5
DESCRIPTION
man
man/simulation.Rd man/helper.Rd man/sbioPN-package.Rd

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.