Team:Evry/Modeling

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Our aim is to understand the trajectory of the auxin molecules in the tadpole's organism. Therefore, we will model this trajectory by a double approach; a continous one and an agent-based one. The continous one, being more general, will help us to determine parameters of the agent based one.
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<center><h1>Modeling a tadpole: a multi-level approach</h1></center>
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<h2>Modeling a system on a complete organism</h2>
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This year, our team decided to tackle a challenging project: creating <i>de novo</i> a new hormonal system in a vertebrate organism. In the modeling part of our work, we were interested in modeling the entire genetic and transport system in the host organism in order to understand the system better as well as to give indications to guide the development of the system in the wet part of our work.
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<p>Modeling a system at the organism level is not an easy task at all. Various approaches and hypothesis have to be used depending on the scale you want to look at and the question you ask. In our work, we used a large combination of classical synthetic biology modeling techniques to look at the system from the organism to the molecular level, using analytical and modeling techniques involving biochemical models, diffusion and transport models using simultaneously and in conjunction Ordinary Differential Equations (ODEs), Partial Differential equations (PDEs) and Agent Based simulations (AB).
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<img src="https://static.igem.org/mediawiki/2012/6/62/MathFrog.png" width=150px>
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<p>This schematic represents the different parts of the models we have created, as well as general information on the modeling methods used in these models. </p>
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<h4>Click on the different elements of this image to access the different models:</h4>
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<img id=ModMap src="https://static.igem.org/mediawiki/2012/e/e4/Schematic_modelingV4.png" width="945" height="829" border="0" class="mapper" usemap="#map" align="center" />
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<area shape="rect" class="noborder icolor474747" coords="240,120,665,210" href="ODE_model" />
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<area shape="rect" class="noborder icolor474747" coords="240,225,665,315" href="auxin_pde" />
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<area shape="rect" class="noborder icolor474747" coords="240,330,665,450" href="Auxin_diffusion" />
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<area shape="rect" class="noborder icolor474747" coords="240,495,665,600" href="auxin_production" />
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<area shape="rect" class="noborder icolor474747" coords="240,615,665,690" href="auxin_detection" />
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<area shape="rect" class="noborder icolor474747" coords="240,705,665,795" href="plasmid_splitting" />
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<area shape="rect" class="noborder icolor474747" coords="790,410,935,460" href="model_integration" />
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<h2>Preparing the work of the future generations on iGEMers working on complex organism</h2>
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<p>When writing down our work, we have made an especial effort for our models and hypothesis to be very understandable, in order to help the work of the future generation of iGEMers working on tadpoles, and on multicellular organisms in general. You can access general informations on the models by clicking on the ODE, PDE and AB simulations on the image below, and all the instructions are provided for you to run our simulations either on your own computer or directly in your web browser (!) using the full power of the Java Applets created using the Netlogo program.</p>
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<p>We hope our work will be useful for other to learn, enjoy and create new models for their projects in the future!</p>
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<h2>Parameters estimation</h2>
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<p>A great part of our modeling work has been to find or estimate the values of the parameters used in the model. For a better readability, we created a special pages regrouping them all.
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<a class="moredetails" target="_blank" href="https://2012.igem.org/Team:Evry/parameters">More details here...</a></p>
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<p id="references">References:</p>
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<li><i> An introduction to agent-based modeling: Modeling natural, social and engineered complex systems with NetLogo</i>, Wilensky, U., & Rand, W. (in press), Cambridge, MA: MIT Press</li>
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Latest revision as of 04:00, 27 September 2012

Modeling a tadpole: a multi-level approach


Modeling a system on a complete organism


This year, our team decided to tackle a challenging project: creating de novo a new hormonal system in a vertebrate organism. In the modeling part of our work, we were interested in modeling the entire genetic and transport system in the host organism in order to understand the system better as well as to give indications to guide the development of the system in the wet part of our work.


Modeling a system at the organism level is not an easy task at all. Various approaches and hypothesis have to be used depending on the scale you want to look at and the question you ask. In our work, we used a large combination of classical synthetic biology modeling techniques to look at the system from the organism to the molecular level, using analytical and modeling techniques involving biochemical models, diffusion and transport models using simultaneously and in conjunction Ordinary Differential Equations (ODEs), Partial Differential equations (PDEs) and Agent Based simulations (AB).

This schematic represents the different parts of the models we have created, as well as general information on the modeling methods used in these models.

Click on the different elements of this image to access the different models:



Preparing the work of the future generations on iGEMers working on complex organism


When writing down our work, we have made an especial effort for our models and hypothesis to be very understandable, in order to help the work of the future generation of iGEMers working on tadpoles, and on multicellular organisms in general. You can access general informations on the models by clicking on the ODE, PDE and AB simulations on the image below, and all the instructions are provided for you to run our simulations either on your own computer or directly in your web browser (!) using the full power of the Java Applets created using the Netlogo program.

We hope our work will be useful for other to learn, enjoy and create new models for their projects in the future!

Parameters estimation

A great part of our modeling work has been to find or estimate the values of the parameters used in the model. For a better readability, we created a special pages regrouping them all. More details here...

References:

  1. An introduction to agent-based modeling: Modeling natural, social and engineered complex systems with NetLogo, Wilensky, U., & Rand, W. (in press), Cambridge, MA: MIT Press

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