Team:USP-UNESP-Brazil/Project1
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- | == '''Overall project''' == | + | == '''Overall project - Associative Memory Network Using Bacteria ''' == |
Since we are a big team and it's our first participation on iGEM, we have two projects going on at the same time. The first one is "Associative Memory Network Using Bacteria" and "Plug&Play Plasmid" | Since we are a big team and it's our first participation on iGEM, we have two projects going on at the same time. The first one is "Associative Memory Network Using Bacteria" and "Plug&Play Plasmid" | ||
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pattern and choose between two systemic memories inserted on the communication network. | pattern and choose between two systemic memories inserted on the communication network. | ||
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== Project Details== | == Project Details== |
Revision as of 20:00, 18 July 2012
Contents |
Overall project - Associative Memory Network Using Bacteria
Since we are a big team and it's our first participation on iGEM, we have two projects going on at the same time. The first one is "Associative Memory Network Using Bacteria" and "Plug&Play Plasmid"
Associative Memory Network Using Bacteria
The memory storage in biological systems has a critical role in biotechnology development. A systemic way of storing a specific memory that can be recovered and used at any moment is studied in several experiments and mathematical models involving neural networks. One of these models, known by “Hopfield Network”, considers the memory storage as a neurons association that shares a characteristic pattern of “communication intensity” – the “measure unity” of a neuron network . This model is notorious for allowing systems the recognizing of patterns.
In this project we propose the genesis of aa communication network using E.coli populations, in order to create a system with associative memory ,like a Hopfield Model. Genetically different populations will be generated and isolated from each other, keeping contact by means of Quorum Sensing Substances (QSS). These QSS will be responsible by inhibition or excitation of pre-determined populations, measuring the amount of excitation by means of GFP fluorescent level. The final objective is to achieve a specific complete pattern of excited and inhibited populations by means of the interactions between bacteria populations, based on an given incomplete pattern. The network will behave in way of recognizing this pattern and choose between two systemic memories inserted on the communication network.