Team:Groningen
From 2011.igem.org
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==Count coli - a synthetic biological counter== | ==Count coli - a synthetic biological counter== | ||
- | <html><center><div style="width: 500px; text-align: justify">Our project aims to design a genetic device able to count and memorize the occurrences of an input signal. We achieved this by | + | <html><center><div style="width: 500px; text-align: justify">Our project aims to design a genetic device able to count and memorize the occurrences of an input signal. We achieved this by utilizing auto-inducing loops that act as memory units, and an engineered riboregulator acting as an AND gate. The design of the device is modular allowing free change of both input and output signals. Each increase of the counter results in a different output signal. The design allows implementation of any number of memory units, as the AND gate design enables us to extend the system in a hassle-free way. In order to tweak bistable autoinducing loops we needed a very fast and robust method for characterizing parts. For this we have created a cloud based application hosting a genetic algorithm . It also allows the combination of data from multiple experiments across models with overlapping components. This functionality, massively parallelized on the cloud and backed by our own pool of clients, allowed us to find parameters of the parts used in the design. |
- | In order to tweak bistable autoinducing loops we | + | |
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Revision as of 23:59, 21 September 2011
Welcome to the iGEM 2011 Groningen team page
Count coli - a synthetic biological counter
Our project aims to design a genetic device able to count and memorize the occurrences of an input signal. We achieved this by utilizing auto-inducing loops that act as memory units, and an engineered riboregulator acting as an AND gate. The design of the device is modular allowing free change of both input and output signals. Each increase of the counter results in a different output signal. The design allows implementation of any number of memory units, as the AND gate design enables us to extend the system in a hassle-free way. In order to tweak bistable autoinducing loops we needed a very fast and robust method for characterizing parts. For this we have created a cloud based application hosting a genetic algorithm . It also allows the combination of data from multiple experiments across models with overlapping components. This functionality, massively parallelized on the cloud and backed by our own pool of clients, allowed us to find parameters of the parts used in the design.
Our engineered biological abacus counting occurrences of cold shocks.