Getting Started
Download the GUI and simulation programs, licensed under the
GNU GPL.
To run the GUI, you will need the following:

Features
 More efficiently simulates the stochastic dynamics by describing the system as a hybrid coupled jump/continuous Markov process
 Solves the resulting system of chemical Langevin and differential Jump equations using either fixed or adaptive stochastic numerical
integrators
 Automatic and dynamic partitioning of the system of bio/chemical reactions
 No a priori knowledge of separation of timescales needed
 Accuracy of solution governed by wellcharacterized stochastic numerical integrators of SDEs
 Supports many rate laws. Additional rate laws are easily added
 Supports nonMarkovian events, such as gamma or Gaussian distributed transitions
 Cell replication is included as a discrete event occurring at Gaussian distributed replication times
 Combinatorial exploration of kinetic parameters and initial conditions
 System perturbations of both kinetic parameters and species concentrations
 Uses the NetCDF file format: Enables fast write/read of extremely large model and solution data sets
 Targetted production platforms: MPIcapable clusters running Linux (other platforms supported on demand)
 An easytouse (but simple) Graphical User Interface is available to quickly define systems of bio/chemical reactions
 Solution data may be directly read into MATLAB or other scientific softwares, analyzed, and plotted for high research productivity

Documentation
Questions, comments, suggestions? Email me. (Address is below)
Bug Alerts!
 Attempting to use the GUI's Plot solution window when the solution variable exists, but contains no data, results in a Matlab Java
exception (crash!). I suggest using the NetCDF Toolbox to analyze solution data.

News
 February 26th, 2006: The article "Multiscale Hy3S: Hybrid stochastic simulation for supercomputers" appears in BMC Bioinformatics. We hope that this article
provides a detailed explanation of how the HyJCMSS methods work. We expect, though, that the Hy3S project will continue to evolve, adding more advanced algorithms and
useful features. And, remember, this is an open source project: feel free to reuse code, but please reference this project if you do. Feel free to contact us with
any questions about the code or the algorithms. Thank you!
 October 20th, 2005: Massive additions: Added three additional ways to numerical integrate the SDEs, including the fixed time step
Milstein method (1st order strong accuracy) and adaptive time step methods using Brownian bridges with either the EulerMaruyama or Milstein
integrators. There's now a total of 5 different algorithms for computing the stochastic dynamics of reaction networks (10 if you include MPI
parallelized versions). In order to accommodate all of the different methods, we went back to using compiler declarative statements within the
source that turns on/off different parts of the code instead of creating many different versions of the source code. Consequently, the Makefile
only works for the Intel Fortran compiler for Linux. Many other compilers support simple declarative statements so adapting the code for other
systems should not be too difficult. The changes are in the CVS tree, but binaries for x86 and ia64 will be released shortly.
 More News!
Examples  Natural and Synthetic Systems
List of Examples
 Update: The examples from the BMC Bioinformatics paper have been added.
