Difference between revisions of "Team:UNOTT/Model"
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<h5>In order to achieve these aims, it was decided to create an image comparing software as well as an internal development environment where members can easily add their own code as well as access other code made by others and other files. </h5> | <h5>In order to achieve these aims, it was decided to create an image comparing software as well as an internal development environment where members can easily add their own code as well as access other code made by others and other files. </h5> | ||
| − | <h5> <a href="https://2017.igem.org/Team:UNOTT/CultureModelling">Find out more about our software /a> </h5> | + | <h5> <a href="https://2017.igem.org/Team:UNOTT/CultureModelling">Find out more about our software </a> </h5> |
<h5> <a href="https://github.com/BurgundyIsAPublicEnemy/iGEMNotts2017/blob/master/LuciferA.c">This environment can be downloaded from our GitHub page</a> </h5> | <h5> <a href="https://github.com/BurgundyIsAPublicEnemy/iGEMNotts2017/blob/master/LuciferA.c">This environment can be downloaded from our GitHub page</a> </h5> | ||
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Revision as of 10:11, 4 September 2017
Overview
When developing Key.Coli, we found it was important to mathematically model possible situations so we could investigate the effects of different situations we might encounter throughout different stages of development as well as during implementation. Software was developed to compare the fluorescence levels with the mother colony to check if there was a high enough degree of similarity.
This information was used by the wet lab to assist them by informing them in what to expect. This was done through the use of programming to create visual graphs, simulations as well as development of tools to allow for comparing between fluorescence levels to be done without needing to create anymore synthetic organisms as well as being far quicker.
The source code for these models can be accessed from our GitHub pageThe models weren't perfect at first: refinement from lab results helped to optimize and correct the models
