Difference between revisions of "Team:Manchester/Model"

 
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<h3>★  ALERT! </h3>
 
<p>This page is used by the judges to evaluate your team for the <a href="https://2017.igem.org/Judging/Medals">medal criterion</a> or <a href="https://2017.igem.org/Judging/Awards"> award listed above</a>. </p>
 
<p> Delete this box in order to be evaluated for this medal criterion and/or award. See more information at <a href="https://2017.igem.org/Judging/Pages_for_Awards"> Instructions for Pages for awards</a>.</p>
 
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<h1> Modeling</h1>
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<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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<h3> Gold Medal Criterion #3</h3>
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To complete for the gold medal criterion #3, please describe your work on this page and fill out the description on your <a href="https://2017.igem.org/Judging/Judging_Form">judging form</a>. To achieve this medal criterion, you must convince the judges that your team has gained insight into your project from modeling. You may not convince the judges if your model does not have an effect on your project design or implementation.
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Please see the <a href="https://2017.igem.org/Judging/Medals"> 2017 Medals Page</a> for more information.
 
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To compete for the <a href="https://2017.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://2017.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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<h5> Inspiration </h5>
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<h2 class="border" style="margin-top: 5vh; text-align: center">Modelling</h2>
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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">Manchester 2016</a></li>
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<li><a href="https://2016.igem.org/Team:TU_Delft/Model">TU Delft 2016  </li>
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<li><a href="https://2014.igem.org/Team:ETH_Zurich/modeling/overview">ETH Zurich 2014</a></li>
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<li><a href="https://2014.igem.org/Team:Waterloo/Math_Book">Waterloo 2014</a></li>
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<p>We used modelling in three ways to inform different parts of the project:</p>
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<p style="margin-left: 40px">1. The statistical Design of Experiments (DoE) was used to design the most efficient experiments to determine the factors influencing the expression of our key enzyme. Two rounds of DoE enabled us to identify the optimal conditions for testing of our experimental system.</p>
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<p style="margin-left: 40px">2. Continuous culture modelling was used to predict the rate at which Phosphostore devices could be produced on different substrates. This allowed us to estimate the yearly cost of treating wastewater using phosphostore. As a result we performed a major re-design of the intended Phosphostore device, assessing the cost reduction potential of different growth conditions and experimental strategies by computational modelling.</p>
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<p style="margin-left: 40px">3. An innovative ensemble modelling approach was used to predict the behaviour of our recombinant phosphate starvation operon in addition to native PHO regulon as a regulatory system for controlling microcompartment synthesis. This helped us to choose the appropriate regulatory parts for our experimental design.</p>
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<a href="https://2017.igem.org/Team:Manchester/Model/DoE"><img src="https://static.igem.org/mediawiki/2017/8/8d/T--Manchester--DOElogo.jpg" width="100%"/></a>
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<p style="text-align: center" "font-size: 24px!important"><b>Design of Experiments</b></p>
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<a href="https://2017.igem.org/Team:Manchester/Model/Continuous_Culture"><img src="https://static.igem.org/mediawiki/2017/5/59/T--Manchester--Chemostat_logo.png"/></a>
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<p style="text-align: center" "font-size: 24px!important"><b>Continuous Culture</b></p>
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<a href="https://2017.igem.org/Team:Manchester/Model/PSO"><img src="https://static.igem.org/mediawiki/2017/1/10/T--Manchester--Operon_logo.jpg" width="100%"/></a>
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<p style="text-align: center" "font-size: 24px!important"><b>Phosphate Starvation Operon</b></p>
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Latest revision as of 18:44, 31 October 2017

Modelling


We used modelling in three ways to inform different parts of the project:

1. The statistical Design of Experiments (DoE) was used to design the most efficient experiments to determine the factors influencing the expression of our key enzyme. Two rounds of DoE enabled us to identify the optimal conditions for testing of our experimental system.

2. Continuous culture modelling was used to predict the rate at which Phosphostore devices could be produced on different substrates. This allowed us to estimate the yearly cost of treating wastewater using phosphostore. As a result we performed a major re-design of the intended Phosphostore device, assessing the cost reduction potential of different growth conditions and experimental strategies by computational modelling.

3. An innovative ensemble modelling approach was used to predict the behaviour of our recombinant phosphate starvation operon in addition to native PHO regulon as a regulatory system for controlling microcompartment synthesis. This helped us to choose the appropriate regulatory parts for our experimental design.


Design of Experiments


Continuous Culture


Phosphate Starvation Operon