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

 
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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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<div class="column full_size">
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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>
  
<img class="full_size_image" style="margin-top:-250px" src="https://static.igem.org/mediawiki/2018/3/3f/T--SCUT-ChinaA--mo.png">
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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>
  
 
<div class="column full_size">
 
<div class="column full_size">
<h2 style="text-align: left">Abstract</h2>
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<h2 style="text-align: left">Input</h2>
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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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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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</div>
  
<p>
 
  
While building our model, we developed a software tool to help us find the optimal solution. After we finished, we modified the software and made it universal, which means it can be used by other researchers.
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<h2 style="text-align: left">Output</h2>
  
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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>
 
</div>
  
 
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<div class="column full_size">
<div class="column two_thirds_size">
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<p style="text-align: justify">
<table>  
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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:
<tr>
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</p>
<th> enzyme </th> <th> Substrate </th> <th> Turnover Number [1/s] </th> <th> KM Value [mM] </th>
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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">
<td> ERG10</td> <td>acetyl-CoA</td> <td>2.1</td> <td>0.33</td> </tr>
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<tr>
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<td> ERG13</td> <td>acetoacetyl-CoA, acetyl-CoA</td> <td>4.6</td> <td>acetoacetyl-CoA:0.0014, acetyl-CoA:0.05</td> </tr>
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<tr>
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<td> HMG1</td> <td>hydroxymethylglutaryl-CoA</td> <td>0.023</td> <td>0.045</td> </tr>
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<tr>
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<td>ERG12</td> <td>mevalonate</td> <td>2.36</td> <td>0.012</td> </tr>
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<tr>
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<td> ERG8</td> <td>phosphomevalonate</td> <td>3.4</td> <td>0.0042</td> </tr>
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<tr>
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<td>ERG19</td> <td>(R,S)-5-diphosphomevalonate</td> <td>5.9</td> <td>0.0091</td> </tr>
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<tr>
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<td> NDPS1</td> <td>isopentenyl diphosphate</td> <td>0.14</td> <td>0.047</td> </tr>
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</table>
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</div>
 
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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">
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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: