A cell is composed of many intertwined regulatory and signaling networks. Proteins, RNA, and DNA act upon one another to control cellular processes and responses to changes in the environment. In this module, we study a model of a synthetic regulatory circuit, the Repressilator, which consists of a loop of three proteins, each of which represses the transcription of the next (akin to the rock-paper-scissors game). As in the Stochastic Cells module, we compare stochastic and deterministic representations of the Repressilator dynamics, here in a much more complex system, where good software design allows seamless conversion between two very different simulation strategies. We also study the difference between shot noise and telegraph noise.

Procedure

• Download the file RepressilatorHints.py and rename it "Repressilator.py".
• Open this file in a text editor (kate or emacs -- we recommend against using kedit) or load it into the IPython dashboard (started with ipython notebook --pylab inline.
• Open a terminal window, move to the correct directory and start ipython, or click on the notebook in the dashboard. You will find it convenient to start python with the --pylab flag -- ie type ipython --pylab or ipython notebook --pylab.
• Follow the directions in Repressilator Exercise