Difference between revisions of "Team:SCUT-ChinaA/Software"

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<div class="column full_size judges-will-not-evaluate">
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<div class="clear"></div>
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<h3>★  ALERT! </h3>
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<div class="igem_content_wrapper">
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<p>This page is used by the judges to evaluate your team for the <a href="https://2018.igem.org/Judging/Medals">medal criterion</a> or <a href="https://2018.igem.org/Judging/Awards"> award listed below</a>. </p>
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<img class="full_size_image" style="margin-top:-360px" src="https://static.igem.org/mediawiki/2018/7/70/T--SCUT-ChinaA--title3-2.png">
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<p> Delete this box in order to be evaluated for this medal criterion and/or award. See more information at <a href="https://2018.igem.org/Judging/Pages_for_Awards"> Instructions for Pages for awards</a>.</p>
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<p style="text-align: justify">
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As you can see in the model page, we have successfully used our model to help us design our experiment. If you are interested in our model, you can use our python software tool and even modify it if you like. You can find it on the GitHub.
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<p style="text-align: justify"><a href="https://github.com/scutzhuzh/optool">Click Here!</a></p>
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<div class="column full_size">
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<h1>Software</h1>
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<h2 style="text-align: left">Input</h2>
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<div class="column full_size">
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<p style="text-align: justify">
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What you need:
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</p>
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<ul>
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<li>
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A complete metabolic pathway, and convert it into a mathematical form, a matrix \(S\) .
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</li>
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<li>
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The constants of the enzymes. Usually you need to put the \(k_{cat}\) and the \(E_t\) in.
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</li>
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</ul>
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<p>You can find more details on how to use this software tool on README.md</p>
 
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<h3>Best Software Tool Special Prize</h3>
 
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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 honor such "nuggets" of computational work.
 
  
  
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To compete for the <a href="https://2018.igem.org/Judging/Awards">Best Software Tool prize</a>, please describe your work on this page and also fill out the description on the <a href="https://2018.igem.org/Judging/Judging_Form">judging form</a>.
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<h2 style="text-align: left">Output</h2>
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<br><br>
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You must also delete the message box on the top of this page to be eligible for this prize.
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<p style="text-align: justify">
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What you will get is a figure like this:
 
</p>
 
</p>
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</div>
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<div class="column half_size">
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<img  src="https://static.igem.org/mediawiki/2018/5/56/T--SCUT-ChinaA--modelresult.jpg">
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</div>
  
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<div class="column full_size">
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<p style="text-align: justify">
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The ordinate indicates the multiple of the predicted product generation rate of the model, and the sequence below the abscissa indicates the priority of the enzymes (the left is the highest).
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</p>
 
</div>
 
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<div class="highlight decoration_A_full">
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<p style="text-align: justify">
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<h3> Inspiration </h3>
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You can also watch the software tool running as the picture below shows, and at the end the software tool will predict the rate of producing your product:
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<p>
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Here are a few examples from previous teams:
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</p>
 
</p>
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<ul>
 
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<li><a href="https://2016.igem.org/Team:BostonU_HW">2016 BostonU HW</a></li>
 
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<li><a href="https://2016.igem.org/Team:Valencia_UPV">2016 Valencia UPV</a></li>
 
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<li><a href="https://2014.igem.org/Team:Heidelberg/Software">2014 Heidelberg</a></li>
 
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<li><a href="https://2014.igem.org/Team:Aachen/Project/Measurement_Device#Software">2014 Aachen</a></li>
 
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</ul>
 
 
</div>
 
</div>
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<div class="column full_size">
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<img  src="https://static.igem.org/mediawiki/2018/1/16/T--SCUT-ChinaA--pythonjietu.png">
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<div class="column full_size">
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<img class="full_size_image" style="margin-top:200px" src="https://static.igem.org/mediawiki/2018/0/0e/T--SCUT-ChinaA--bottom.png">
 
</div>
 
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</html>
 
</html>

Latest revision as of 00:49, 18 October 2018

SCUT-ChinaA

As you can see in the model page, we have successfully used our model to help us design our experiment. If you are interested in our model, you can use our python software tool and even modify it if you like. You can find it on the GitHub.

Click Here!

Input

What you need:

  • A complete metabolic pathway, and convert it into a mathematical form, a matrix \(S\) .
  • The constants of the enzymes. Usually you need to put the \(k_{cat}\) and the \(E_t\) in.

You can find more details on how to use this software tool on README.md

Output

What you will get is a figure like this:

The ordinate indicates the multiple of the predicted product generation rate of the model, and the sequence below the abscissa indicates the priority of the enzymes (the left is the highest).

You can also watch the software tool running as the picture below shows, and at the end the software tool will predict the rate of producing your product: