Difference between revisions of "Team:Bielefeld-CeBiTec/Project/Modeling"

 
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<div class="container text_header"><h3> Modeling </h3></div>
 
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<div class="container text_header"><h1>Modeling</h1></div>
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As biological research studies are more and more based on both, laboratory research and mathematical computations, we decided to follow this encouraging development and, thus, build a mathematical model of our system. This abstract representation of a biological process has the purpose to understand the underlying functionality in the first place. Moreover, a variety of distinct conditions can easily be tested and arbitrarily often repeated. Once the feedback loop between model and experiment has led to a satisfying validation, the model can be applied to predict specific biological events of interest. New knowledge can be achieved very quickly.
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<div class="container text_header"><h3>The Model</h3></div>
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To model the key features of our project, the <a href="https://2016.igem.org/Team:Bielefeld-CeBiTec/Project/Selection/Bacterial_Two-Hybrid_System">selection system</a> and the [growth model], we decided to use two models in correspondence. Thus, the development becomes more facile and transparent and the models can be used separately. In the following the workflow of our connected models is shown:
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<figcaption>Figure 1: Workflow of the modeling process. <br> The interaction of the selection model (model&thinsp;I) and the competition model (model&thinsp;II) are shown. From left to right: The selection model produces a reproduction rate <i>r</i> - with every run. After several runs the different reproduction rates are transferred to the competition model, which translates these rates into growth curves.</figcaption>
 
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First, the selection system was implemented (model&thinsp;I). The basic structure is based on <a href="https://2011.igem.org/Team:Potsdam_Bioware/Project/Details_Modeling">iGEM Potsdam</a>&apos;s modeling work of 2011. The model&thinsp;I represents the [bacterial two hybrid selection system] and produces the reproduction rate <i>r</i> of a single cell with a given affinity under selection pressure with ampicillin (amp). The reproduction rate is computed for many different affinities and then transmitted to the competition model (model&thinsp;II). The competition model depicts the growth behavior of different adapted <i>E. colis</i> in one flask under multiple inoculations.
 
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Latest revision as of 19:10, 16 October 2016



Modeling

As biological research studies are more and more based on both, laboratory research and mathematical computations, we decided to follow this encouraging development and, thus, build a mathematical model of our system. This abstract representation of a biological process has the purpose to understand the underlying functionality in the first place. Moreover, a variety of distinct conditions can easily be tested and arbitrarily often repeated. Once the feedback loop between model and experiment has led to a satisfying validation, the model can be applied to predict specific biological events of interest. New knowledge can be achieved very quickly.

The Model

To model the key features of our project, the selection system and the [growth model], we decided to use two models in correspondence. Thus, the development becomes more facile and transparent and the models can be used separately. In the following the workflow of our connected models is shown:

Modeling Workflow
Figure 1: Workflow of the modeling process.
The interaction of the selection model (model I) and the competition model (model II) are shown. From left to right: The selection model produces a reproduction rate r - with every run. After several runs the different reproduction rates are transferred to the competition model, which translates these rates into growth curves.

First, the selection system was implemented (model I). The basic structure is based on iGEM Potsdam's modeling work of 2011. The model I represents the [bacterial two hybrid selection system] and produces the reproduction rate r of a single cell with a given affinity under selection pressure with ampicillin (amp). The reproduction rate is computed for many different affinities and then transmitted to the competition model (model II). The competition model depicts the growth behavior of different adapted E. colis in one flask under multiple inoculations.