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Team:Mexico-UNAM-IPN
From 2008.igem.org
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| - | [[Team:Mexico-UNAM-IPN/ | + | [[Team:Mexico-UNAM-IPN/Horizontal_Transfer| <font face="trebuchet ms" style="color:#2171B7"> '''<big>Horizontal Transfer</big>''' </font>]] |
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| - | [[Team:Mexico-UNAM-IPN/ | + | [[Team:Mexico-UNAM-IPN/Turing_Patterns| <font face="trebuchet ms" style="color:#2171B7"> '''<big>Turing Patterns</big>''' </font>]] |
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| - | [[ | + | [[Team:Mexico-UNAM-IPN/About_us| <font face="trebuchet ms" style="color:#2171B7"> '''<big>About us</big>''' </font>]] |
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| - | [[Team:Mexico-UNAM-IPN/Suplemental| <font face="trebuchet ms" style="color:#2171B7"> '''Suplemental''' </font>]] | + | [[Team:Mexico-UNAM-IPN/Suplemental| <font face="trebuchet ms" style="color:#2171B7"> '''<big>Suplemental</big>''' </font>]] |
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Horizontal gene transfer is an evolutionary mechanism that contributes to the acquisition of new genetic material among organisms; as such it helps bacteria to acquire antibiotic resistance and other genetic devices. The main goal is to design a devise that would detect events of horizontal gene transfer among bacteria. | Horizontal gene transfer is an evolutionary mechanism that contributes to the acquisition of new genetic material among organisms; as such it helps bacteria to acquire antibiotic resistance and other genetic devices. The main goal is to design a devise that would detect events of horizontal gene transfer among bacteria. | ||
| - | Genetically modified E. coli were monitored until a detectable sign appears in the media, indicating an event of horizontal transfer. In order to detect such events, we will use plasmids as the genetic material that could be transferred in a bacterial culture. </font></big> | + | Genetically modified E. coli were monitored until a detectable sign appears in the media, indicating an event of horizontal transfer. In order to detect such events, we will use plasmids as the genetic material that could be transferred in a bacterial culture. </font></big> |
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We are trying to reproduce Turing patterns using a genetic network. These spatial structures could in principle be generated by perturbing equilibrium configurations by the action of diffusion. | We are trying to reproduce Turing patterns using a genetic network. These spatial structures could in principle be generated by perturbing equilibrium configurations by the action of diffusion. | ||
| - | Although many mathematical models have been built based on these ideas in order to reproduce what is observed in biological systems, the identification of the actual substances that create the patterns (morphogenes) is still not clear. We propose a different approach, namely, to implement a genetic network in order to recover Turing patterns in | + | Although many mathematical models have been built based on these ideas in order to reproduce what is observed in biological systems, the identification of the actual substances that create the patterns (morphogenes) is still not clear. We propose a different approach, namely, to implement a genetic network in order to recover Turing patterns in a biological system[https://static.igem.org/mediawiki/2008/d/df/Saludos.JPG .] </font></big> |
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<!-- END TURING PATTERNS HEADER--> | <!-- END TURING PATTERNS HEADER--> | ||
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| + | [[Image:MacroproyectoLarge.JPG]] | ||
| + | </center> | ||
Latest revision as of 02:53, 30 October 2008
| Horizontal Transfer | Turing Patterns |
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Horizontal gene transfer is an evolutionary mechanism that contributes to the acquisition of new genetic material among organisms; as such it helps bacteria to acquire antibiotic resistance and other genetic devices. The main goal is to design a devise that would detect events of horizontal gene transfer among bacteria. Genetically modified E. coli were monitored until a detectable sign appears in the media, indicating an event of horizontal transfer. In order to detect such events, we will use plasmids as the genetic material that could be transferred in a bacterial culture.
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We are trying to reproduce Turing patterns using a genetic network. These spatial structures could in principle be generated by perturbing equilibrium configurations by the action of diffusion. Although many mathematical models have been built based on these ideas in order to reproduce what is observed in biological systems, the identification of the actual substances that create the patterns (morphogenes) is still not clear. We propose a different approach, namely, to implement a genetic network in order to recover Turing patterns in a biological system.
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