Team:Grenoble/Projet/Modelling

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<h2>JB</h2>
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since they evolve both in time and space. To help future teams with similar calculations, we explain
since they evolve both in time and space. To help future teams with similar calculations, we explain
in details the algorithms that were used and provide the scripts <a href="http://igemgrenoble-files.perso.sfr.fr/2011/MATLAB_Archives/">here</a>.
in details the algorithms that were used and provide the scripts <a href="http://igemgrenoble-files.perso.sfr.fr/2011/MATLAB_Archives/">here</a>.
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The modelling results are described in the last section.
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The modelling results are described in the last section.<br/><br/>
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For an introduction to the modelling of biological genetic circuit see our tutorials in the human practice
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section or  them here :
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<ul>
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<li>
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<a href="https://static.igem.org/mediawiki/2011/9/91/M_for_B.png">
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Modelling for biologist</a>
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</li>
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<li>
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<a href="https://static.igem.org/mediawiki/2011/5/54/B_for_M.png">
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Synthetic Biology for modellers</a>
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</li>
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</ul>
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<br/><br/>
<br/><br/>
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  <a href="https://2011.igem.org/Team:Grenoble/Projet/Modelling/Deterministic" ><img class="icon" src="https://static.igem.org/mediawiki/2011/b/b4/Icon_deterministic.png"/></a>
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  <a href="https://2011.igem.org/Team:Grenoble/Projet/Modelling/Deterministic" ><img class="icon" src="https://static.igem.org/mediawiki/2011/0/01/Bouton_model_construction.png"/></a>
     
     
      <big><big><a href="https://2011.igem.org/Team:Grenoble/Projet/Modelling/Deterministic" class="menu">Construction of the model :</a></big></big><br/>
      <big><big><a href="https://2011.igem.org/Team:Grenoble/Projet/Modelling/Deterministic" class="menu">Construction of the model :</a></big></big><br/>
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<a class="menu" href="https://2011.igem.org/Team:Grenoble/Projet/Modelling/Deterministic#Our_algorithms">Our algorithms</a><br/><br/><br/>
<a class="menu" href="https://2011.igem.org/Team:Grenoble/Projet/Modelling/Deterministic#Our_algorithms">Our algorithms</a><br/><br/><br/>
       
       
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  <a href="https://2011.igem.org/Team:Grenoble/Projet/Modelling/Stochastic"><img class="icon" src="https://static.igem.org/mediawiki/2011/6/67/Icon_stochastic.png"/></a>
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  <a href="https://2011.igem.org/Team:Grenoble/Projet/Modelling/Stochastic"><img class="icon" src="https://static.igem.org/mediawiki/2011/c/c7/Bouton_model_stochastic.png"/></a>
   
   
<big><big><a class="menu" href="https://2011.igem.org/Team:Grenoble/Projet/Modelling/Stochastic">Stochastic Modelling :</a></big></big><br/>
<big><big><a class="menu" href="https://2011.igem.org/Team:Grenoble/Projet/Modelling/Stochastic">Stochastic Modelling :</a></big></big><br/>
       
       
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<a class="menu" href="https://2011.igem.org/Team:Grenoble/Projet/Modelling/Stochastic#Geof">Sensitivity to noise</a><br/>
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<a class="menu" href="https://2011.igem.org/Team:Grenoble/Projet/Modelling/Stochastic#Geof">Sensitivity to noise: a first approach</a><br/>
<a class="menu" href="https://2011.igem.org/Team:Grenoble/Projet/Modelling/Stochastic#Gillespie_algorithm">Gillespie algorithm</a><br/>
<a class="menu" href="https://2011.igem.org/Team:Grenoble/Projet/Modelling/Stochastic#Gillespie_algorithm">Gillespie algorithm</a><br/>
<a class="menu" href="https://2011.igem.org/Team:Grenoble/Projet/Modelling/Stochastic#Stats">Mean, standard deviation and statistical properties</a><br/><br/>
<a class="menu" href="https://2011.igem.org/Team:Grenoble/Projet/Modelling/Stochastic#Stats">Mean, standard deviation and statistical properties</a><br/><br/>
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  <a href="https://2011.igem.org/Team:Grenoble/Projet/Modelling/Parameters"><img class="icon" src="https://static.igem.org/mediawiki/2011/3/34/Icon_parameters.png"/></a>
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  <a href="https://2011.igem.org/Team:Grenoble/Projet/Modelling/Parameters"><img class="icon" src="https://static.igem.org/mediawiki/2011/b/ba/Bouton_model_parameter.png"/></a>
   
   
<big><big><a class="menu" href="https://2011.igem.org/Team:Grenoble/Projet/Modelling/Parameters">Parameters</a></big></big><br/>
<big><big><a class="menu" href="https://2011.igem.org/Team:Grenoble/Projet/Modelling/Parameters">Parameters</a></big></big><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#Table">Table of parameters</a><br/>
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<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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<br/><br/>
    </p>
    </p>
     
     
    <p>
    <p>
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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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You can find our modelling results <a href="https://2011.igem.org/Team:Grenoble/Projet/Results">here</a>.
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{{:Team:Grenoble/Design/pied}}

Latest revision as of 02:20, 29 October 2011

Grenoble 2011, Mercuro-Coli iGEM


Modelling

The modelling team is responsible for:

  1. Verifying that the designed genetic circuit elicits the desired behavior in E coli. A deterministic model of the circuit has been developed in order to predict the dynamical behavior of the circuit in the presence of a concentration gradient of IPTG and various concentrations of Mercury or aTc (anhydrotetracycline).
  2. Providing specifications for the quantification device (size, number of bacteria, IPTG gradient). The apparition of the red line indicating the presence and quantity of Mercury or aTc is sensitive to fluctuations in the concentration of these molecules and IPTG. We took into account these fluctuations in a stochastic version of the circuit model, which we have used to determine the specifications of our device.

Table of content

In the following pages, we detail the development of the deterministic and stochastic models, together with their dynamical analysis. Solving numerically these systems required tricky calculations, since they evolve both in time and space. To help future teams with similar calculations, we explain in details the algorithms that were used and provide the scripts here. The modelling results are described in the last section.

For an introduction to the modelling of biological genetic circuit see our tutorials in the human practice section or them here :



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


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

Parameters
Table of parameters


You can find our modelling results here.

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iGEM 2011 Main Page


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