Difference between revisions of "Team:TU Darmstadt/Project"

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Our team also kept working on parts from previous years and provided the registry with improved versions of a protein scaffold. By attaching proteins that are related in “genetic?” pathways in close proximity to each other onto a scaffold the metabolic rate can be improved significantly.  
 
Our team also kept working on parts from previous years and provided the registry with improved versions of a protein scaffold. By attaching proteins that are related in “genetic?” pathways in close proximity to each other onto a scaffold the metabolic rate can be improved significantly.  
 
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The laboratory work was supported by our modeling group incorporating simulations for the <font color="red">Pleas fill in the name</font> membrane and computational structure prediction techniques to design a <font color="red">Pleas fill in the name</font> hokD Killswitch. In the process, we developed a new structure prediction technique based on an artificial neural network and implemented a genetic algorithm to design arbitrary RNA riboswitches. we made the program available to the community as <a href="#">Web service</a> on our server.
 
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Revision as of 17:13, 18 September 2015

iGEM TU Darmstadt 2015

''Building with light opens up a spectrum of opportunities, especially if you can build in three dimensions. Why don't use this potential to help people in need.''


Our project combined very different ideas from various fields into a massive interdisciplinary project. Aspects of computational engineering, additive manufacturing and of course synthetic biology were combined into our project ‘Building with light - TU Darmstadt 2015’.

In cooperation with our partner Synenergene we developed an application scenario, which focuses on the interpendency of our scheduled project with the community and how both parties can be affected by each other. Thereby we were able to optimize our project appropriate to the needs of the general public. This approach punctuates the main idea of Synenergene to deal with “responsible research and innovation in synthetic biology”.

We were able to establish genetic pathways via metabolic engineering in E.coli that allow the bacterium to produce various chemicals that can be used for 3D-printing purposes, namely ethylene glycol, itaconic acid and xylitol.
 Our team also kept working on parts from previous years and provided the registry with improved versions of a protein scaffold. By attaching proteins that are related in “genetic?” pathways in close proximity to each other onto a scaffold the metabolic rate can be improved significantly.

The laboratory work was supported by our modeling group incorporating simulations for the Pleas fill in the name membrane and computational structure prediction techniques to design a Pleas fill in the name hokD Killswitch. In the process, we developed a new structure prediction technique based on an artificial neural network and implemented a genetic algorithm to design arbitrary RNA riboswitches. we made the program available to the community as Web service on our server.

Last year we were able to reduce the amount of money we spend on lab materials by printing gel chambers with a 3D-printer, as well as several other open hardware devices. This year we went even further and decided to create a functional stereolithography 3D-printer from scratch.

Aside from all the work in the laboratory and workshop fabrication laboratory Synergene gave us a helping hand to develop an applicable approach for our ‘Policy & Practices’ project.