Team:Alberta

From 2013.igem.org

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    <div class="titlebar">
 +
<br/>
 +
<img src="/wiki/images/4/41/Ab_mapmen_title.png" width="600" height="95"></img><img src="/wiki/images/a/a5/2013-igem-logo.png" width="198" height="95"></img>
 +
 
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    </div>
 +
    <div class="bin">
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      <ul class="navbar">
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        <li><i class="nav-icon"></i><a href="/Team:Alberta" class="active">Home</a></li>
 +
        <li><a id="project" href="#"">Project</a>
 +
          <ul>
 +
            <li><a href="/Team:Alberta/Background">Background</a></li>
 +
            <li><a href="/Team:Alberta/Overview">Overview</a></li>
 +
            <li><a href="/Team:Alberta/Results">Results</a></li>
 +
            <li><a href="/Team:Alberta/Protocols">Protocols</a></li>
 +
            <li><a href="/Team:Alberta/Parts">Submitted Parts</a></li>
 +
            <li><a href="/Team:Alberta/Accomplishments">Accomplishments</a></li>
 +
          </ul>
 +
        </li>
 +
        <li><a id="team" href="#">Team</a>
 +
          <ul>
 +
            <li><a href="/Team:Alberta/Team">Roster</a></li>
 +
            <li><a href="https://igem.org/Team.cgi?year=2013&team_name=Alberta">Official Profile</a></li>
 +
            <li><a href="/Team:Alberta/Sponsors">Sponsors</a></li>
 +
            <li><a href="/Team:Alberta/Attributions">Attributions</a></li>
 +
          </ul>
 +
        </li>
 +
        <li><a id="humanpractices" href="#">Human Practices</a>
 +
          <ul>
 +
            <li><a href="/Team:Alberta/Outreach">Outreach</a></li>
 +
            <li><a href="/Team:Alberta/Community">Community</a></li>
 +
          </ul>
 +
        </li>
 +
        <li><a href="/Team:Alberta/MainSafety">Safety</a>
 +
          <ul>
 +
            <li><a href="/Team:Alberta/SafetyForm">Safety Form</a></li>
 +
            <li><a href="/Team:Alberta/FAQ">FAQ</a></li>
 +
            <li><a href="/Team:Alberta/Resources">Resources</a></li>
 +
          </ul>
 +
        </li>
 +
      <div class="igem-bar"><a href="https://2013.igem.org"><img src="/wiki/images/a/ad/IGem-logo.png"></img></a></div>
 +
      </ul>
 +
      <div class="sidebar">
 +
        <div class="sidebar_block">
 +
<br>
 +
<img src=" /wiki/images/2/2d/Background_icon.png " align="left" width="50" height="50"></img>Curious about the possibilities of biocomputing? Need of a crash course on travelling salesman problems? Visit our <a href="https://2013.igem.org/Team:Alberta/Background">background page</a> for more information on the real-world applications of our project.
 +
<br>
 +
<br>
 +
<img src="/wiki/images/thumb/b/bf/Workings_icon.png/610px-Workings_icon.png " align="left" width="50" height="50"></img>
 +
Want to get straight to the details of what Team Alberta has been working on this summer? Read up in the <a href="https://2013.igem.org/Team:Alberta/Overview">overview</a> and <a href="https://2013.igem.org/Team:Alberta/Results">results</a> pages to see what we've achieved.
 +
<br>
 +
<br>
 +
      <img src=" /wiki/images/thumb/f/f6/Peoples_icon.png/618px-Peoples_icon.png" align="left" width="50" height="50"></img>Or maybe you'd like to get to know the team itself, those who have helped us along and those we've helped in turn? See the <a href="https://2013.igem.org/Team:Alberta/Team">team roster</a>, <a href="https://2013.igem.org/Team:Alberta/Attributions">sponsors</a> and <a href="https://2013.igem.org/Team:Alberta/Outreach">outreach</a> pages to meet everyone who's participated.
 +
        </div>
 +
      </div>
 +
      <div class="main">
 +
      <!--div class="block">
 +
        <img src="/wiki/images/e/e8/Mapmaker-banner.jpg"></img>
 +
      </div-->
 +
      <div class="block">
 +
        <h3 class="centered">
 +
          Welcome to the Team Alberta website! Our project pushes the limits of Synthetic Biology to create massively parallel, highly selective biological computers.
 +
        </h3><br />
 +
        <img src="/wiki/images/e/e8/Mapmaker-banner.jpg"
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          style="width:85%;"></img>
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Team Alberta represents the University of Alberta, from Edmonton. Our project is called "The Littlest Mapmakers", and is an attempt to create a biological computer capable of solving the Traveling Salesman Problem!</center></font></strong></html>
 
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The traveling salesman problem is a mathematical optimization problem that was first formally described in 1930, and has been intensively studied in the computer sciences as a benchmark for optimization algorithms. The problem asks:
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In our project, we use DNA to compute solutions by converting all of the elements of the problem into representative sequences of DNA: cities become selectable marker genes (specifically, antibiotic resistance genes), paths between the cities become short, sticky-ended linkers (each of which is only able to ligate to two specific “city” strands), and the distance of a given path is represented by the concentration of the corresponding linker in solution. These pieces of DNA are successively ligated together to produce plasmids that act as “maps”, where the order in which the genes appear in the plasmid describes a route travelling to the various cities in the problem.
 
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[[Image:sample_product.png|300px]][[Image:sample_route.png|600px]]
 
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The resulting plasmids are transformed into a bacterial culture, so that we can select for only those plasmids that include every city in the list. Then, plasmid DNA is extracted from the surviving bacterial colonies and analyzed to determine which plasmid (and thus which route) occurred the most frequently. This route, the one most favoured by the ligation reactions, is the optimal route!
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<html><p><font size=4><strong><center>
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Team Alberta represents the University of Alberta, from Edmonton. Our project, "The Littlest Mapmakers", is an attempt to create a biological computer capable of solving the Traveling Salesman Problem</p></center></font></strong></html>
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<font size=3>The traveling salesman problem is a mathematical optimization problem that was first formally described in 1930, and has been intensively studied in the computer sciences as a benchmark for optimization algorithms. The problem asks:
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Given a set of cities (or other destinations), and a list of the distances (or the travel time, fuel consumption, et cetera) between each pair of those cities, what is the shortest possible route that travels to every city exactly once, and then returns to the origin city?</div>
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</div>
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</html>
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In our project, we use DNA to compute solutions by converting all of the elements of the problem into representative sequences of DNA: cities become selectable marker genes (specifically, antibiotic resistance genes), paths between the cities become short, sticky-ended linkers (each of which is only able to ligate to two specific “city” strands), and the distance of a given path is represented by the concentration of the corresponding linker in solution. These pieces of DNA are successively ligated together to produce plasmids that signify “routes”, where the order in which the genes appear in the plasmid indicates the order in which the cities are visited. 
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{|align="center"
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|[[Image:sample_product.png|300px]][[Image:sample_route.png|650px]]
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<html><font size=3>The resulting plasmids are transformed into a bacterial culture, so that we can select for only those plasmids that include every city in the list. Then, plasmid DNA is extracted from the surviving bacterial colonies and analyzed to determine which plasmid (and thus which route) occurred the most frequently. This route, the one most favoured by the ligation reactions, is the optimal route!</font></html>
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{| style="color:#1b2c8a;background-color:#0c6;" cellpadding="3" cellspacing="1" border="1" bordercolor="#fff" width="62%" align="center"
{| style="color:#1b2c8a;background-color:#0c6;" cellpadding="3" cellspacing="1" border="1" bordercolor="#fff" width="62%" align="center"
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!align="center"|[[Team:Alberta/Attributions|Attributions]]
!align="center"|[[Team:Alberta/Attributions|Attributions]]
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<html><a class="twitter-timeline" href="https://twitter.com/iGEMAlberta" data-widget-id="368908364702437377">Tweets by @iGEMAlberta</a>
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Latest revision as of 03:38, 29 October 2013



Curious about the possibilities of biocomputing? Need of a crash course on travelling salesman problems? Visit our background page for more information on the real-world applications of our project.

Want to get straight to the details of what Team Alberta has been working on this summer? Read up in the overview and results pages to see what we've achieved.

Or maybe you'd like to get to know the team itself, those who have helped us along and those we've helped in turn? See the team roster, sponsors and outreach pages to meet everyone who's participated.

Welcome to the Team Alberta website! Our project pushes the limits of Synthetic Biology to create massively parallel, highly selective biological computers.


Retrieved from "http://2013.igem.org/Team:Alberta"