Difference between revisions of "Team:KUAS Korea/DryLab/Conclusion"
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| − | + | <td class="align-middle text-center section-header"><h3>Modeling Results & Conclusion</h3></td> | |
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| − | + | <h4><strong>Modeling results</strong></h4> | |
| − | + | <ol>We coded python for our mathematical mode. We can change the parameter values.<br><br> | |
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| − | <center><img src="https://static.igem.org/mediawiki/2018/b/ba/T--KUAS_Korea--code_epsilon.png" height=" | + | <center><img src="https://static.igem.org/mediawiki/2018/b/ba/T--KUAS_Korea--code_epsilon.png" height="600px" allowfullscreen> |
<br>[Fig 1] Python code</center><br><br> | <br>[Fig 1] Python code</center><br><br> | ||
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| − | + | We plotted graph by this python code, and these are results. We changed glucose capture efficiency value for each graph. In graph orange shows cheater's growth rate, and blue graph shows the cooperator's growth rate.<br><br> | |
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| − | <center><img src="https://static.igem.org/mediawiki/2018/0/08/T--KUAS_Korea--epsilon.png" height=" | + | <center><img src="https://static.igem.org/mediawiki/2018/0/08/T--KUAS_Korea--epsilon.png" height="350px" align="center" allowfullscreen> |
<br>[Fig 2] curve of epsilon is 0.002<br><br></center> | <br>[Fig 2] curve of epsilon is 0.002<br><br></center> | ||
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| − | <center><img src="https://static.igem.org/mediawiki/2018/d/db/T--KUAS_Korea--epsilon_two.png" height=" | + | <center><img src="https://static.igem.org/mediawiki/2018/d/db/T--KUAS_Korea--epsilon_two.png" height="350px" align="center" allowfullscreen> |
<br>[Fig 3] Curve of epsilon = 0.2 <br><br><br></center> | <br>[Fig 3] Curve of epsilon = 0.2 <br><br><br></center> | ||
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| − | <center><img src="https://static.igem.org/mediawiki/2018/9/9c/T--KUAS_Korea--epsilon_eight.png" height=" | + | <center><img src="https://static.igem.org/mediawiki/2018/9/9c/T--KUAS_Korea--epsilon_eight.png" height="350px" align="center" allowfullscreen> |
<br>[Fig 4] Curve of epsilon = 0.8 <br><br><br></center> | <br>[Fig 4] Curve of epsilon = 0.8 <br><br><br></center> | ||
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| − | + | Then we changed the value of epsilon continuously. | |
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| − | <center><img src="https://static.igem.org/mediawiki/2018/ | + | <center><img src="https://static.igem.org/mediawiki/2018/b/b1/T--KUAS_Korea--code_rainbow.png" height="600px" align="center" allowfullscreen> |
| − | <br>[Fig | + | <br>[Fig 5] code which plot the rainbow curve</center> |
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| − | And | + | If epsilon is 0, shows the blue cheater graph. And if epsilon is 1, shows the red cheater graph. |
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| + | <center><img src="https://static.igem.org/mediawiki/2018/0/0c/T--KUAS_Korea--epsilon_rainbow.png" height="350px" align="center" allowfullscreen> | ||
| + | <br>[Fig 5] Graph of epsilon changing continuously</center><br><br> | ||
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| − | + | As a result, cheater growth is higher than value c. Also if glucose efficiency increase cheater need more cooperator to reach the maximum growth | |
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<br><br><br> | <br><br><br> | ||
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| − | < | + | <h4><strong>Conclusion</strong></h4> |
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| − | + | We can change the value of the parameters. In our case we changed the epsilon value. Cheater is the dominant species in the co-culture environment. But epsilon value increases, cheater need more cooperators. But in the end, cheater and cooperator maintain certain concentration in co-culture. Because only cooperator can make glucose, which is the only essential substance for cheater and cooperator. | |
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Latest revision as of 01:42, 18 October 2018
Modeling Results & Conclusion |
Modeling results
- We coded python for our mathematical mode. We can change the parameter values.
[Fig 1] Python code
We plotted graph by this python code, and these are results. We changed glucose capture efficiency value for each graph. In graph orange shows cheater's growth rate, and blue graph shows the cooperator's growth rate.
[Fig 2] curve of epsilon is 0.002
[Fig 3] Curve of epsilon = 0.2
[Fig 4] Curve of epsilon = 0.8
[Fig 5] code which plot the rainbow curve
If epsilon is 0, shows the blue cheater graph. And if epsilon is 1, shows the red cheater graph.
[Fig 5] Graph of epsilon changing continuously
Conclusion
We can change the value of the parameters. In our case we changed the epsilon value. Cheater is the dominant species in the co-culture environment. But epsilon value increases, cheater need more cooperators. But in the end, cheater and cooperator maintain certain concentration in co-culture. Because only cooperator can make glucose, which is the only essential substance for cheater and cooperator. Sponsors
