File: ExamplesLacOperon.htm

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<html>
<head>
<title>Lac Operon</title>
</head>
<body>
<h1>Lac Operon</h1>

<p>
Consider the lac operon model presented in Section 7.5 of
<a href="http://www.staff.ncl.ac.uk/d.j.wilkinson/smfsb/">Stochastic
Modelling for Systems Biology</a>. 
Open the file <tt>examples/cain/WilkinsonSMfSB/ch07-lac-stoch.xml</tt> 
and generate a trajectory. Note that the method uses the a Python solver 
that is capable of simulating events. As this is not a high performance 
solver, generating a trajectory will take a couple of minutes. So launch
the simulation now and then continue reading.
</p>

<p>
When the trajectory has been generated, open the plot configuration
window by clicking the plot button <img src="plot.png">&nbsp; in the
output panel.  First unselect all of the species by right-clicking on
the &quot;Show&quot; column header. Then select the Rna, Z, and
Lactose species. Next left-click on the &quot;Line Color&quot; header
to color these three species with different hues. Unselect the
&quot;Legend&quot; toggle, we will enter the species names in the Y
axis label. Select a custom figure size of 8 by 2 inches. Now we are
prepared to plot each of the three species in a separate window by
selecting each in turn. The resulting plot configuration window is
shown below.
</p>

<p align="center">
<img src="ExamplesLacOperonPlotWindow.png">
</p>

<p>
This model has a time event: at time <i>t</i> = 20,000, the amount of Lactose 
is increased by 10,000. The interesting feature of this model is how the
system responds to the influx of Lactose. The plots below reproduce the
results in the text.
</p>

<p align="center">
<img src="LacOperonLactose.jpg">
</p>

<p align="center">
<img src="LacOperonRna.jpg">
</p>

<p align="center">
<img src="LacOperonZ.jpg">
</p>


</body>
</html>