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<html>
<head>
<title>Welcome</title>
</head>
<body>
<p align="right">
<img src="cain.png">
</p>
<h1>Welcome</h1>
<p>
This is version 1.10 of Cain, developed by Sean Mauch,
<img src="seanEmail.png">, at the <a href="http://www.cacr.caltech.edu/">
Center for Advanced Computing Research</a>, at the
<a href="http://www.caltech.edu/">California Institute of Technology</a>.
</p>
<p>
Cain performs stochastic and deterministic simulations of chemical
reactions. It can spawn multiple simulation processes to utilize
multi-core computers. It stores models, methods, and simulation
output (populations and reaction counts)
in an XML format. In addition, <a href="http://sbml.org/">SBML</a>
models can be imported and exported. The models and methods
can be read from input files or edited within the program.
</p>
<p>
The GUI (Graphical User Interface) is written in
<a href="http://www.python.org/">Python</a> and uses the
<a href="http://www.wxpython.org/">wxPython</a> toolkit.
Most of the solvers are implemented as command line executables, written in
<a href="http://en.wikipedia.org/wiki/C%2B%2B">C++</a>, which are driven
by Cain. This makes it easy to launch batch jobs. It also simplifies the
process of adding new solvers. Cain offers a variety of solvers:
<ul>
<li> Gillespie's direct method.
<li> Gillespie's first reaction method.
<li> Gibson and Bruck's next reaction method.
<li> Tau-leaping.
<li> Hybrid direct/tau-leaping.
<li> ODE integration.
</ul>
</p>
<p>
The reactions may have mass-action kinetic laws or arbitrary
propensity functions. For the latter, custom command line executables are
generated when the simulations are launched. For the former one has the choice
of generating a custom executable or of using one of the built-in mass-action
solvers. Compiling and launching the solvers is done internally; you do not
need to know how to write or compile programs. However, to use the custom
executables your computer must have compiler software. Without a
compiler you can only simulate systems with mass-action kinetics.
</p>
<p>
In addition to the high performance solvers written in C++, Cain has
solvers implemented in Python. These are much slower than the other
solvers, but are able to simulate events.
</p>
<p>
Once you have run a simulation to generate trajectories (possible
realizations of the system) you can visualize the results by plotting
the species populations or reactions counts. You can also view the
output in a table or export it to a spreadsheet.
</p>
<p>
If you are learning about stochastic simulations, I recommend that
you start by reading
<a href="http://www.sbi.uni-rostock.de/publications/books/stochasticapproaches/"</a>Stochastic Approaches for Systems Biology</a> by
<a href="http://www.sbi.uni-rostock.de/team/single/dr-mukhtar-ullah/">Mukhtar
Ullah</a> and
<a href="http://www.sbi.uni-rostock.de/team/single/prof-olaf-wolkenhauer/">Olaf
Wolkenhauer</a> and
<a href="http://www.staff.ncl.ac.uk/d.j.wilkinson/smfsb/">
Stochastic Modelling for Systems Biology</a> by
<a href="http://www.staff.ncl.ac.uk/d.j.wilkinson/">Darren
Wilkinson</a>.
Note that there is a <a href="SAfSB.htm">chapter</a> in this manual
devoted to examples from the former.
</p>
</body>
</html>
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