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

 
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{{SCUT-ChinaA/CSS2}}
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{{SCUT-ChinaA/CSS}}
 
{{SCUT-ChinaA/T3}}
 
{{SCUT-ChinaA/T3}}
 
{{SCUT-ChinaA}}
 
{{SCUT-ChinaA}}
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<html>
 
<html>
  
<div class="column two_thirds_size">
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<table>
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<div class="clear"></div>
<tr>
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<div class="igem_content_wrapper">
<th> enzyme </th> <th> Substrate </th> <th> Turnover Number [1/s] </th> <th> KM Value [mM] </th>
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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">
</tr>  
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<tr>
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<div class="column full_size">
<td> ERG10</td> <td>acetyl-CoA</td> <td>2.1</td> <td>0.33</td> </tr>
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<p style="text-align: justify">
<tr>
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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.
<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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</p>
<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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<p style="text-align: justify"><a href="https://github.com/scutzhuzh/optool">Click Here!</a></p>
<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>
 
</div>
  
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<div class="column full_size">
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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>
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 +
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<div class="column full_size">
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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:
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</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>
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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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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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</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>
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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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</div>
  
 
</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: