Difference between revisions of "Team:Waterloo/Model"
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| − | + | <h2> Modeling</h2> | |
| − | <h2> Modeling</h2> | + | <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> |
| − | <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> | + | <h5> Inspiration </h5> |
| − | + | <p> Here are a few examples from previous teams:</p> | |
| − | <h5> Inspiration </h5> | + | <ul> |
| − | <p> | + | <li><a href="https://2014.igem.org/Team:ETH_Zurich/modeling/overview">ETH Zurich 2014</a></li> |
| − | Here are a few examples from previous teams: | + | <li><a href="https://2014.igem.org/Team:Waterloo/Math_Book">Waterloo 2014</a></li> |
| − | </p> | + | </ul> |
| − | <ul> | + | |
| − | <li><a href="https://2014.igem.org/Team:ETH_Zurich/modeling/overview">ETH Zurich 2014</a></li> | + | |
| − | <li><a href="https://2014.igem.org/Team:Waterloo/Math_Book">Waterloo 2014</a></li> | + | |
| − | </ul> | + | |
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| − | <p>We summarized literature knowledge in order to determine the insertion location that would provide the greatest readthrough efficiency. This was then used to inform the design of our construct.</p> | + | <div align="center"><div class=col-md-4> |
| + | <img class="wcontent-img-solo50" src="https://static.igem.org/mediawiki/2016/9/9f/Cfp_impact_folding.png"/> | ||
| + | </div> | ||
| + | <div class=col-md-8> | ||
| + | <p>We summarized literature knowledge in order to determine the insertion location that would provide the greatest readthrough efficiency. This was then used to inform the design of our construct.</p> | ||
| + | </div> | ||
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Revision as of 20:56, 19 October 2016
Modelling
This page will contain a brief overview for each of the things we modelled this year - it shouldn't be linked from Protein Aggregation on the navbar. We're a good candidate for best model because of the breadth of understanding we accumulated by tackling all of the different aspects of our system, not just because we made a good model of prion aggregation.
Modeling
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.
Inspiration
Here are a few examples from previous teams:
We summarized literature knowledge in order to determine the insertion location that would provide the greatest readthrough efficiency. This was then used to inform the design of our construct.
We modelled the accumulation of amyloids and the curing of the [PSI+] state as a result of Hsp104 overexpression and knockdown.
We modelled the loss rates of yeast plasmids, in order to determine whether we should use a high copy or low copy number plasmid in the lab.
We modelled the effectiveness of applying CRISPR-dCas9 to cause knockdown of Hsp104 expression.
We analysed data from 2015 about collaborations between iGEM teams in order to find patterns. We tried to identify whether there were correlations between variables like team size, success, location, and collaboration in order to make recommendations to future teams.
