Team:USTC-China/modeling

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             <a href="#panel">Modeling</a>
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             <a href="#panel1">Introduction</a>
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                    Color Imaging
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                    Motion Control
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                    Motion Measurement
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                    Conjugation Modeling
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                    C. imager Simulation
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            <a href="#panel3">Cellular Level</a>
 
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    <div class="title"><h1>Introduction</h1></div>
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      <p>In our modeling efforts, we followed closely on our major 2 sub-projects,</p>
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        <p><b>Color Imaging</b> and <b> Motion Control</b></p>
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      <p>and their experimental connection.</p>
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        <p><b>Conjugation</b></p>
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      <p>Combing all the above, came the</p>
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        <p><b>C. imager Modeling.</b></p>
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<img src="https://static.igem.org/mediawiki/2014/f/ff/USTC_intro_model.png" width="500"/>
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      <p>The governing idea is that a model, intrinsically, should stare at the corresponding experiments, at the same time, go boldly beyond it. In this light, we built models not only deeply rooted in the experimental data, but also powerful of making audacious predictions.
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       <p>In the Imaging part and the Motion Control part, we built models to simulate the behaviors of light-sensing, color-printing and motion-control genetic circuits, respectively. </p>
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      <p>On top of that, we attempted to build a procedure bridging the connection between a desired output image and the input image projected onto the bacteria. Also, in-depth modeling about motion control render us penetrating insights, clearly answering the question that how the sticky characteristic of C.C. could contribute to the clearance of output images.</p>
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        <p>In our modeling efforts, we basically focused on three thing:</p>
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      <p>Besides, as the experimental connection between the 2 sub-projects, process of conjugation is highly significant. Therefore, we elaborately established a model to analyze the concentration change of all types of bacterium involved in that process. Founded by concrete parameters extracting from experiments, it produced useful predictions to guide this experiment.
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      <p>Despite the range, amount and power of our models, they also covered many mathematical  & computational methods, ranging from ODE, phase-space analysis, agent-based model to Monte Carlo simulation. Furthermore, a variety types of figures and animations ensure the results vividly displayed.</p>
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<li>Physical Performance of Color Mangling</li>
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<p>All we are trying is to give a insight into the system we are studying, to solve problems like:</p>
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<p>So, we mainly model on four levels: <br />
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1. <strong>Colony level</strong> <br />
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2. <strong>Cellular level</strong> <br />
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3. <strong>Gene level</strong> <br />
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4. <strong>Physical level</strong></p>
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Latest revision as of 03:43, 18 October 2014

Introduction

In our modeling efforts, we followed closely on our major 2 sub-projects,

Color Imaging and Motion Control

and their experimental connection.

Conjugation

Combing all the above, came the

C. imager Modeling.


The governing idea is that a model, intrinsically, should stare at the corresponding experiments, at the same time, go boldly beyond it. In this light, we built models not only deeply rooted in the experimental data, but also powerful of making audacious predictions.


In the Imaging part and the Motion Control part, we built models to simulate the behaviors of light-sensing, color-printing and motion-control genetic circuits, respectively.


On top of that, we attempted to build a procedure bridging the connection between a desired output image and the input image projected onto the bacteria. Also, in-depth modeling about motion control render us penetrating insights, clearly answering the question that how the sticky characteristic of C.C. could contribute to the clearance of output images.


Besides, as the experimental connection between the 2 sub-projects, process of conjugation is highly significant. Therefore, we elaborately established a model to analyze the concentration change of all types of bacterium involved in that process. Founded by concrete parameters extracting from experiments, it produced useful predictions to guide this experiment.


Despite the range, amount and power of our models, they also covered many mathematical & computational methods, ranging from ODE, phase-space analysis, agent-based model to Monte Carlo simulation. Furthermore, a variety types of figures and animations ensure the results vividly displayed.