IGEM:UC Berkeley/2006: Difference between revisions
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[[Berk2006-ConjugationTeam | Conjugation 6/7/06-7/21/06]]<br> | [[Berk2006-ConjugationTeam | Conjugation 6/7/06-7/21/06]]<br> | ||
[[Berk2006-ConjugationTeam2 | Conjugation 7/24/06 - 09/07/06]]<br> | [[Berk2006-ConjugationTeam2 | Conjugation 7/24/06 - 09/07/06]]<br> | ||
[[Berk2006- | [[Berk2006-ConjugationTeam3 | Conjugation 09/07/06- present]]<br> | ||
[[Berk2006-LocksAndKeysTeam | Locks and Keys]]<br> | [[Berk2006-LocksAndKeysTeam | Locks and Keys]]<br> | ||
[[Berk2006-LogicGatesTeam | Logic Gates]]<br> | [[Berk2006-LogicGatesTeam | Logic Gates]]<br> |
Revision as of 10:17, 18 September 2006
A Bacterial model for Neural Learning
Information is assimilated in neural systems by an architecture of cell-based switches interconnected by communication channels. These channels are based on physical, spatial connections between cells in the form of dendrite and axons. We are constructing a bacterial model of neural systems where individual bacteria take the place of neurons and communicate with one another through addressable conjugation. Here, bacteria can send messages to one another via conjugation of plasmid DNAs, but the message is only meaningful to cells with a matching address sequence. In this way, the Watson Crick base-pairing of addressing sequences replaces the spatial connectivity present in neural systems. To construct this system, we have adapted natural conjugation systems as the communication device. Information contained in the transferred plasmids is only accessable by "unlocking" the message using RNA based locks and keys. The resulting addressable conjugation process is being adapted to construct a network of NAND logic gates in bacterial cultures. Ultimately, this will allow us to explore different architectures of neural systems to better understand the mechanisms of learning. |