Category: Release

We are pleased to announce the release of StochSS Version 1.9! StochSS: Stochastic Simulation Service, is an integrated development environment for modeling and simulation of discrete stochastic biochemical systems. An easy-to-use GUI enables researchers to quickly develop and simulate biological models on a desktop or laptop, which can then be expanded or combined to incorporate increasing levels of complexity. As the demand for computational power increases, StochSS is able to seamlessly scale up by deploying cloud computing resources. The software currently supports simulation of ODE and well-mixed discrete stochastic models, parameter estimation of discrete stochastic models, and simulation of spatial stochastic models.
New capabilities of Version 1.9 include:

1. Support for simulation and parameter sweep jobs on batch cluster computing (i.e. Qsub based computing clusters)
2. Configuration of batch computing resources
3. Enhancement to multi-user setup, including email authentication

Click here to download StochSS 1.9 (Legacy) for your platform.

We are pleased to announce the release of StochSS Version 1.8! StochSS: Stochastic Simulation Service, is an integrated development environment for modeling and simulation of discrete stochastic biochemical systems. An easy-to-use GUI enables researchers to quickly develop and simulate biological models on a desktop or laptop, which can then be expanded or combined to incorporate increasing levels of complexity. As the demand for computational power increases, StochSS is able to seamlessly scale up by deploying cloud computing resources. The software currently supports simulation of ODE and well-mixed discrete stochastic models, parameter estimation of discrete stochastic models, and simulation of spatial stochastic models.
New capabilities of Version 1.8 include:

1. Parameter Sweep tool facilitates 1D/2D parameter sweeps for all models
2. Integration of Jupyter Notebooks on job result pages for post-processing analysis
3. Status page updates for filtering and automatic forwarding of running->finished jobs

We are pleased to announce the release of StochSS Version 1.7! 
StochSS: Stochastic Simulation Service,  is an integrated development environment for modeling and simulation of discrete stochastic biochemical systems.  An easy to use GUI enables researchers to quickly develop and simulate biological models on a desktop or laptop, which can then be expanded or combined to incorporate increasing levels of complexity.  As the demand for computational power increases, StochSS is able to seamlessly scale up by deploying cloud computing resources.  The software currently supports simulation of ODE and well-mixed discrete stochastic models, parameter estimation of discrete stochastic models, and simulation of spatial stochastic models.
New capabilities of Version 1.7 include:

•  Volume rendering visualization for spatial jobs.
•  StochSS-launcher uses docker containers to run StochSS. Includes support for newest OSX and Windows operating systems.
•  Added RSS feed to front page
•  Many bug fixes and stability enhancements

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 Lötstedt and Andreas Hellander
Uppsala University

StochSS 1.6 is now officially released!
New capabilities of Version 1.6 include:

• Spatial visualization now supports animation, wireframe rendering, and mesh slicing
• FlexCloud: run ‘cloud’ jobs on dedicated hardware (in addition to using EC2)
• Import SBML models
• Many bug fixes and stability enhancements

Details and instructions on how to obtain the code can be found on the Download page
Tutorials are available on the Documentation page
Linda Petzold and Chandra Krintz
University of California Santa Barbara
Per Lotstedt and Andreas Hellander
Uppsala Universiteit

StochSS 1.5.1 is now officially released!
New in version 1.5.1:

• UI enhancements and stability bug fixes

Details and instructions on how to obtain the code can be found on the Download page
Tutorials are available on the Documentation page
Linda Petzold and Chandra Krintz – University of California Santa Barbara
Per Lötstedt and Andreas Hellander – Uppsala University