Revision as of 14:35, 19 July 2017

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.

Metabolic Modeling

Recent advances in computational biology include whole-genome metabolic networks. They describe the flow of metabolites within a particular organism. Using constraint-based methods allows to make quantitative predictions about the phenotype while eliminating many of the complex parameters. Of particular interest to our project is flux balance analysis (FBA), which allows to predict the biomass flux which is directly correlated with cell growth rate.

ModelSEED

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Gold Medal Criterion #3

To complete for the gold medal criterion #3, please describe your work on this page and fill out the description on your judging form. 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.

Please see the 2017 Medals Page for more information.

Best Model Special Prize

To compete for the Best Model prize, please describe your work on this page and also fill out the description on the judging form. Please note you can compete for both the gold medal criterion #3 and the best model prize with this page.

You must also delete the message box on the top of this page to be eligible for the Best Model Prize.

Inspiration

Here are a few examples from previous teams:

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+<h1> Metabolic Modeling</h1>
+<p> Recent advances in computational biology include <b>whole-genome metabolic networks</b>. They describe the flow of metabolites within a particular organism. Using constraint-based methods allows to make quantitative predictions about the phenotype while eliminating many of the complex parameters. Of particular interest to our project is <b>flux balance analysis (FBA)</b>, which allows to predict the biomass flux which is directly correlated with cell growth rate.  </p>
 <a href="https://2017.igem.org/Team:Virginia/Model/ModelSEED"><h1>ModelSEED</h1></a>