Team:Grenoble/Projet/Modelling

From 2011.igem.org

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<a class="menu" href="https://2011.igem.org/Team:Grenoble/Projet/Modelling/Parameters#Table">Table of parameters</a><br/>
<a class="menu" href="https://2011.igem.org/Team:Grenoble/Projet/Modelling/Parameters#Table">Table of parameters</a><br/>
<a class="menu" href="https://2011.igem.org/Team:Grenoble/Projet/Modelling/Parameters#Sensitivity">Sensitivity to parameters</a><br/><br/><br/>
<a class="menu" href="https://2011.igem.org/Team:Grenoble/Projet/Modelling/Parameters#Sensitivity">Sensitivity to parameters</a><br/><br/><br/>
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  <a href="https://2011.igem.org/Team:Grenoble/Projet/Modelling/Results"><img class="icon" src="https://static.igem.org/mediawiki/2011/e/e1/Icon_results.png"/></a>
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      <big><big><a href="https://2011.igem.org/Team:Grenoble/Projet/Modelling/Results" class="menu">Analysis of the system</a></big></big><br/>
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You can find the results of our modelling results in the <a href="https://2011.igem.org/Team:Grenoble/Projet/Results">results page</a>.
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      <a class="menu" href="https://2011.igem.org/Team:Grenoble/Projet/Modelling/Results#Simulation">Simulation of the bacteria distribution on the plate</a><br/>
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Revision as of 15:16, 25 October 2011

Grenoble 2011, Mercuro-Coli iGEM


Modelling

In the particular case of our circuit and final use of the bacteria, the modelling team had to check the effectiveness of our circuit of course, but also had to give the specificities (size, number of bacteria, IPTG gradient specificities) of the measuring device we intend to produce.

Table of content

In the next pages we first expose technically which algorithms we used for both deterministic modelling and stochastic modelling and explain our MATLAB scripts (available here) in the hope it could help future modelling teams.
We exposed the results in the last section, for anyone who is interested in the results only

Construction of the model :
Establishment of the equation Toggle switchQuorum sensing
Our algorithms


Stochastic Modelling :
Sensitivity to noise
Gillespie algorithm
Mean, standard deviation and statistical properties

Parameters
Table of parameters
Sensitivity to parameters


You can find the results of our modelling results in the results page.

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