Watch the recording from our SIAM-CSE 21 mini-tutorial on March 1st and 2nd, 2021.
StochSS Mini-Tutorial Video- Part 1 Linda Petzold and Brian Drawert
StochSS Mini-Tutorial Video – Part 2 Andreas Hellander, Fredrick Werde, and Brian Drawert
Minitutorial on StochSS Live! recorded at SIAM CSE 21: https://www.siam.org/conferences/cm/conference/cse21
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:
Click here to download StochSS 1.9 (Legacy) for your platform.
We gave a tutorial on StochSS at the International Conference on Systems Biology (ICSB) on August 7th, 2017 hosted by Virginia Tech in Blacksburg, Virginia.
Click here for details.
We will give a tutorial on StochSS at the CSHL Cellular Dynamics & Models meeting on April 11th. See https://meetings.cshl.edu/meetings.aspx?meet=COMP&year=17 for details on this meeting.
We have recently published a paper about StochSS in PLOS Computational Biology. It should be of interest to anyone who wants to know more about how StochSS is designed or how it can be used for modeling and simulation.
Stochastic Simulation Service: Bridging the Gap between the Computational Expert and the Biologist
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:
We will give tutorials on StochSS at the Q-Bio summer school, first in Albuquerque on July 12th and then in Ft. Collins on July 13th. For details, see the Q-Bio website.
We are now providing StochSS as a service on http://try.stochss.org. This means that you can try StochSS without having to install anything locally on your computer.
You have multiple options if you would like to use StochSS on your own resources. The simplest way to get started is to download the binary package (uses Docker).
Our trial server is deployed in the SNIC Science Cloud. If you would like to provide StochSS as a service for your reseach group or for a distributed collaboration, you can do this easily on your own servers, or in another cloud infrastructure provider such as Amazon EC2. MOLNs, another member of the StochSS suite of tools, can help you to configure and deploy an identical setup.
Please do not hesitate to reach out to us if you need help with this process.
Many of you also like the possibility to work with solvers in a programming environment. All of the tools that are powering StochSS are also available as stand alone libraries:
In addition, if you have access to cloud infrastructure, and would like to work in a pre-configured environment powered by a Jupyther Notebook frontend and interactive parallel computing, you should check out MOLNs:
MOLNs: Cloud platform framework for large-scale computational experiments such as ensembles and parameter sweeps, backed by Jupyther and Ipython Parallel.
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:
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:
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
