We are pleased to announce the release of StochSS: Stochastic Simulation Service, Version 1.4. StochSS is an integrated development environment featuring state of the art algorithms for discrete stochastic biochemical simulation. StochSS is designed to enable you to easily scale up your simulations in complexity, deploying compute resources as needed. The current version includes algorithms for simulation of ODEs with sensitivity analysis, well-mixed stochastic systems, and parameter estimation for stochastic systems.
New capabilities of Version 1.4 include spatial stochastic simulation capabilities powered by the PyURDME spatial solver (http://www.pyurdme.org/).
For more details and instructions on how to obtain the code, visit us at www.StochSS.org.
Linda Petzold and Chandra Krintz
University of California Santa Barbara
Per Lotstedt and Andreas Hellander
StochKit: a Stochastic Simulation Toolbox for Biology
StochKit is an efficient, extensible stochastic simulation framework developed in the C++ language that aims to make stochastic simulation accessible to practicing biologists and chemists, while remaining open to extension via new stochastic and multiscale algorithms. The current version of StochKit includes the popular Gillespie Stochastic Simulation Algorithm (SSA) Direct Method, adaptive non-negativity preserving explicit tau-leaping, and core modules for explicit, implicit and trapezoidal tau-leaping methods.
StochKit is supported by grants from NIH, DOE, and the UCSB Institute for Collaborative Biotechnologies (US Army). It is available at Sourceforge.net.
- Differential Algebraic System Solver. DASSL
- DASSL example 1
- DASSL example 2
- Large Scale Differential Algebraic Equation Solver. DASPK2.0
- Window zip format daspk.zip
- Large Scale Differential Algebraic Equation Solver with Sensitivity Analysis. DASPK3.1
- DASSL and DASPK2.0 are available in the public domain.
- DASPK3.1 is subject to copyright restrictions, but is available for research purposes. It may still be subject to revision. This latest version of DASPK3.1 includes the root-finding DAE solver DASKR (root-finding modifications to DASPK3 done by Alan Hindmarsh, LLNL). DASPKAdjoint, which uses the adjoint method for computing the sensitivity coefficients, is also included.