Team:Manchester/Modellingtest
From 2013.igem.org
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- | <center><b>Key Achievements</b><br></center> | + | <center><b><u>Key Achievements</b></u><br></center> |
<center>• Produced iGEM's first ever model based on uncertainty analysis</center> | <center>• Produced iGEM's first ever model based on uncertainty analysis</center> | ||
<center>• Used modelling to directly influence experimental and human practices work</center> | <center>• Used modelling to directly influence experimental and human practices work</center> |
Latest revision as of 18:32, 26 October 2013
Enzymes in the FAB pathway showed a lack of experimentally determined kinetic parameters. To account for this, we used probability distributions for each individual parameter defined with respect to the uncertainty of the value. We were then able to generate not one but a series of unbiased models to illustrate the FAB pathway. We believe that this innovative approach to modelling appropriately addresses uncertainties in biology and is important for use in future computational investigations.
Trying to experimentally study the overexpression of some enzymes critically involved in palm oil synthesis, as predicted by our “system” level model isn’t easy, particularly when they are involved in cyclic reactions (eg FAB pathway). Our strategy was to simply add a His-tag to the N- and C-terminus of βHACdH, but to make it even more complex βHACdH is a homodimer. Therefore, we did another model but this time of the molecular dynamics kind to see which terminal, if any, would be best to add the His-tags to.
As part of our Human Practices investigations, we created a series of in depth population dynamics models to show the impact that the palm oil industry has on the population of the Sumatran Orangutan. We were then able to project this into the future to demonstrate a series of likely scenarios. Sadly, things are looking pretty bleak for the Orangutan - however, it appears there could be a way to save them...
Here at Manchester iGEM team, we believe that modelling is a vital step in the production of any synthetic biology system. However, often the production of such models can be hindered or left out altogether due to lack of expertise and outside help. With this in mind, we enlisted the help of another two UK iGEM teams in a quest to educate the iGEM community about the software available to them.