Difference between revisions of "Team:WashU StLouis/Software"

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{{WashU_StLouis}}
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        <a class="navbar-brand page-scroll" href="#page-top">Nitrogenius</a>
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<h2>Software</h2>
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      <!-- Collect the nav links, forms, and other content for toggling -->
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            <a class="page-scroll" href="#parts_list">Software</a>
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          </li>
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          <li>
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            <a href="mailto:ayekedavidr@wustl.edu?subject=Bug">Report Bugs</a>
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  <!-- Project Overview -->
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    <section id="software" class="row bg-white sectionNum1">
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      <h2>Singe Gene Knockout Softwares</h2>
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      <p>The Penn State team created a python script to perform single gene knockouts, and determin which genes gave greater metabolic values.</p>
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      <h4>Workflow</h4>
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      <ol>
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        <li>
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          <p>Create a list of all genes, constructed from the provided GPRs in the genome scale model.</p>
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        </li>
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        <p>Create lists of reactions that will be deleted for each gene knockout. This is done by evaluating each reaction GPR for each gene. If a gene is essential to a given GPR, the reaction is added to the list of reactions which will be deleted for that knockout.  </p>
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        </li>
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        <li>
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          <p>Given a list of deleted reactions for each gene, FBA is run iteratively for each gene knockout. Running FBA will determine maximum biomass, max and min ATP values, and max and min flavodoxin values. </p>
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        </li>
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          <p>The FBA results are collected and outputted for further analysis. </p>
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        </li>
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      </ol>
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      <p>The code can be found <a href="https://github.com/Dacode45/SingleGeneKO">here</a></p>
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    </section>
  
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<h4>Note</h4>
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<p>In order to be considered for the <a href="https://2015.igem.org/Judging/Awards#SpecialPrizes">Best Software Tool award</a>, you must fill out this page.</p>
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</div>
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<p>Regardless of the topic, iGEM projects often create or adapt computational tools to move the project forward. Because they are born out of a direct practical need, these software tools (or new computational methods) can be surprisingly useful for other teams. Without necessarily being big or complex, they can make the crucial difference to a project's success. This award tries to find and honour such "nuggets" of computational work.</p>
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<p>
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If you are working on software as your main project, please join the software track. If you are creating software as an addition to your main project, please apply for this award.
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</p>
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<p>
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Here are a few examples from previous teams:
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</p>
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<ul>
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<li><a href="https://2013.igem.org/Team:TU-Munich/Results/Software">TU Munich 2013</a></li>
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<li><a href="https://2014.igem.org/Team:Heidelberg/Software">Heidelberg 2014</a></li>
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<li><a href="https://2014.igem.org/Team:Aachen/Project/Measurement_Device#Software">Aachen 2014</a></li>
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</ul>
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</div>
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{{:Team:WashU_StLouis/Footer}}

Latest revision as of 00:42, 18 September 2015

Washington University - Penn State iGEM

Welcome To Our Website!
WashU and Penn State   iGEM 2015
Project Description Let's Talk Apply for the 2016 iGEM Team!

Singe Gene Knockout Softwares

The Penn State team created a python script to perform single gene knockouts, and determin which genes gave greater metabolic values.

Workflow

  1. Create a list of all genes, constructed from the provided GPRs in the genome scale model.

  2. Create lists of reactions that will be deleted for each gene knockout. This is done by evaluating each reaction GPR for each gene. If a gene is essential to a given GPR, the reaction is added to the list of reactions which will be deleted for that knockout.

  3. Given a list of deleted reactions for each gene, FBA is run iteratively for each gene knockout. Running FBA will determine maximum biomass, max and min ATP values, and max and min flavodoxin values.

  4. The FBA results are collected and outputted for further analysis.

The code can be found here