Team:Grenoble/Projet/Modelling
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<br/><big><big><a class="menu" href="https://2011.igem.org/Team:Grenoble/Projet/Modelling/Parameters">Parameters</a></big></big><br/><br/><br/><br/> | <br/><big><big><a class="menu" href="https://2011.igem.org/Team:Grenoble/Projet/Modelling/Parameters">Parameters</a></big></big><br/><br/><br/><br/> | ||
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<big><big><a href="https://2011.igem.org/Team:Grenoble/Projet/Modelling/Results" class="menu">Results :</a></big></big><br/> | <big><big><a href="https://2011.igem.org/Team:Grenoble/Projet/Modelling/Results" class="menu">Results :</a></big></big><br/> |
Revision as of 20:05, 21 September 2011
Modelling
Table of content
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.
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
Deterministic Modelling :
Our equations and how we obtained them : Toggle switchQuorum sensing
Our algorithms
Isoclines and Hysteresis
Stochastic Modelling :
Geoffrey
Gillespie algorithm
Mean, standard deviation and statistical properties
Parameters
Results :
Validation of our genetical network
Device