Difference between revisions of "Team:ECUST/Model"

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    <div id="bannerquote">Model</div>
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<h1 class="box-heading">Quorum sensing model</h1>
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<p>To understand, predict and ultimately control the behavior of our engineered microbial group effect, we have developed dynamic model of the system, based on differential equations which describe and integrate the individual processes. This model involves several entities going from the molecular level (genes, RNAs, proteins, and metabolites) up to the cellular and population levels, distinct intracellular and extracellular compartments, and a wide range of biological and physical processes (transcription, translation, signalling, growth, diffusion, etc). Here we can show the concentrate of DspB and Enterobactin produced by our engineered bacteria and the biofilm and rust removing time through calculating.</p>
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<p><a target="_blank" style="color:white; text-decoration:underline;" href="https://2018.igem.org/Team:ECUST/Quorum_Sensing"><i>Click here to learn more.</i></a><p>
  
 
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<h3>★  ALERT! </h3>
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<p>This page is used by the judges to evaluate your team for the <a href="https://2018.igem.org/Judging/Medals">medal criterion</a> or <a href="https://2018.igem.org/Judging/Awards"> award listed below</a>. </p>
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<p> Delete this box in order to be evaluated for this medal criterion and/or award. See more information at <a href="https://2018.igem.org/Judging/Pages_for_Awards"> Instructions for Pages for awards</a>.</p>
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<h1> Modeling</h1>
 
 
<p>Mathematical models and computer simulations provide a great way to describe the function and operation of BioBrick Parts and Devices. Synthetic Biology is an engineering discipline, and part of engineering is simulation and modeling to determine the behavior of your design before you build it. Designing and simulating can be iterated many times in a computer before moving to the lab. This award is for teams who build a model of their system and use it to inform system design or simulate expected behavior in conjunction with experiments in the wetlab.</p>
 
  
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<h1 class="box-heading">Fur-cecropin AD model </h1>
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<p>Furthermore, in order to measure the ability of engineered bacteria to kill <i>iron bacteria</i> and the work time our bacteria needed to collapse the iron system, we developed another model which is used to descrip the production of the cecropin AD and the sterilizing ability of the cecropin. This model includes three parts: the iron sensor, the inverter system, the sterilizing system. The sensor model tells the concentrate of Fe2+ when our bacteria start working. The inverter system shows the cecropin productin and the sterilize system demonstrates the sterilization effect. The model makes the function with above all parts.</p>
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<p><a target="_blank" style="color:white; text-decoration:underline;" href="https://2018.igem.org/Team:ECUST/Iron_Sensing"><i>Click here to learn more.</i></a><p>
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<h3> Gold Medal Criterion #3</h3>
 
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Convince the judges that your project's design and/or implementation is based on insight you have gained from modeling. This could be either a new model you develop or the implementation of a model from a previous team. You must thoroughly document your model's contribution to your project on your team's wiki, including assumptions, relevant data, model results, and a clear explanation of your model that anyone can understand.
 
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The model should impact your project design in a meaningful way. Modeling may include, but is not limited to, deterministic, exploratory, molecular dynamic, and stochastic models. Teams may also explore the physical modeling of a single component within a system or utilize mathematical modeling for predicting function of a more complex device.
 
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Please see the <a href="https://2018.igem.org/Judging/Medals"> 2018
 
Medals Page</a> for more information.
 
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<h3>Best Model Special Prize</h3>
 
  
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To compete for the <a href="https://2018.igem.org/Judging/Awards">Best Model prize</a>, please describe your work on this page  and also fill out the description on the <a href="https://2018.igem.org/Judging/Judging_Form">judging form</a>. Please note you can compete for both the gold medal criterion #3 and the best model prize with this page.
 
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You must also delete the message box on the top of this page to be eligible for the Best Model Prize.
 
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<h3> Inspiration </h3>
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Here are a few examples from previous teams:
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<li><a href="https://2016.igem.org/Team:Manchester/Model">2016 Manchester</a></li>
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<li><a href="https://2016.igem.org/Team:TU_Delft/Model">2016 TU Delft</li>
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<li><a href="https://2014.igem.org/Team:ETH_Zurich/modeling/overview">2014 ETH Zurich</a></li>
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<li><a href="https://2014.igem.org/Team:Waterloo/Math_Book">2014 Waterloo</a></li>
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Latest revision as of 23:21, 17 October 2018

Model

Quorum sensing model

To understand, predict and ultimately control the behavior of our engineered microbial group effect, we have developed dynamic model of the system, based on differential equations which describe and integrate the individual processes. This model involves several entities going from the molecular level (genes, RNAs, proteins, and metabolites) up to the cellular and population levels, distinct intracellular and extracellular compartments, and a wide range of biological and physical processes (transcription, translation, signalling, growth, diffusion, etc). Here we can show the concentrate of DspB and Enterobactin produced by our engineered bacteria and the biofilm and rust removing time through calculating.

Click here to learn more.

Fur-cecropin AD model

Furthermore, in order to measure the ability of engineered bacteria to kill iron bacteria and the work time our bacteria needed to collapse the iron system, we developed another model which is used to descrip the production of the cecropin AD and the sterilizing ability of the cecropin. This model includes three parts: the iron sensor, the inverter system, the sterilizing system. The sensor model tells the concentrate of Fe2+ when our bacteria start working. The inverter system shows the cecropin productin and the sterilize system demonstrates the sterilization effect. The model makes the function with above all parts.

Click here to learn more.