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<a href="https://2020.igem.org/Team:XMU-China/Parts"><li>Parts</li></a> | <a href="https://2020.igem.org/Team:XMU-China/Parts"><li>Parts</li></a> | ||
<a href="https://2020.igem.org/Team:XMU-China/Contribution"><li>Contributions</li></a> | <a href="https://2020.igem.org/Team:XMU-China/Contribution"><li>Contributions</li></a> | ||
− | <a href="https://2020.igem.org/Team:XMU-China/Engineering"><li> | + | <a href="https://2020.igem.org/Team:XMU-China/Engineering"><li>Engineering Success</li></a> |
<a href="https://2020.igem.org/Team:XMU-China/Improve"><li>Improve</li></a> | <a href="https://2020.igem.org/Team:XMU-China/Improve"><li>Improve</li></a> | ||
</ul> | </ul> | ||
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<a href="" class="a1">Awards</a> | <a href="" class="a1">Awards</a> | ||
<ul class="two"> | <ul class="two"> | ||
+ | <a href="https://2020.igem.org/Team:XMU-China/Awards"><li>Awards</li></a> | ||
<a href="https://2020.igem.org/Team:XMU-China/Judging"><li>Judging</li></a> | <a href="https://2020.igem.org/Team:XMU-China/Judging"><li>Judging</li></a> | ||
<a href="https://2020.igem.org/Team:XMU-China/Human_Practices"><li>Best Integrated Human Practices</li></a> | <a href="https://2020.igem.org/Team:XMU-China/Human_Practices"><li>Best Integrated Human Practices</li></a> | ||
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<a href="https://2020.igem.org/Team:XMU-China/Model"><li>Best Model</li></a> | <a href="https://2020.igem.org/Team:XMU-China/Model"><li>Best Model</li></a> | ||
<a href="https://2020.igem.org/Team:XMU-China/Hardware"><li>Best Hardware</li></a> | <a href="https://2020.igem.org/Team:XMU-China/Hardware"><li>Best Hardware</li></a> | ||
− | <a href="https://2020.igem.org/Team:XMU-China/ | + | <a href="https://2020.igem.org/Team:XMU-China/Parts#Basic"><li>Best Basic Parts</li></a> |
− | + | <a href="https://2020.igem.org/Team:XMU-China/Parts#Composite"><li>Best Composite Parts</li></a> | |
− | + | <a href="https://2020.igem.org/Team:XMU-China/Parts#Collection"><li>Best Part Collection</li></a> | |
</ul> | </ul> | ||
</li> | </li> | ||
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<p>This year XMU-China aims at developing an efficient glyphosate detection and degradation system. The degradation system plans to disintegrate glyphosate into be AMPA to minimize the toxicity. It is meaningful and time-saving to guide us in operating our experiment through establishing an appropriate model. </p> | <p>This year XMU-China aims at developing an efficient glyphosate detection and degradation system. The degradation system plans to disintegrate glyphosate into be AMPA to minimize the toxicity. It is meaningful and time-saving to guide us in operating our experiment through establishing an appropriate model. </p> | ||
<p>We developed a further interaction with CSU_CHINA on the modeling of mutated phnJ, and then our team found an easy way to compute the binding energy between our mutation and the endogenous C-P lyase with Rosetta, which enabled us to model on personal computers equipped with normal hardware. Also, CSU_CHINA suggested us to rent a server to run MD to enhance the accuracy of the model.</p> | <p>We developed a further interaction with CSU_CHINA on the modeling of mutated phnJ, and then our team found an easy way to compute the binding energy between our mutation and the endogenous C-P lyase with Rosetta, which enabled us to model on personal computers equipped with normal hardware. Also, CSU_CHINA suggested us to rent a server to run MD to enhance the accuracy of the model.</p> | ||
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</section> | </section> | ||
<section id="PS3" class="js-scroll-step"> | <section id="PS3" class="js-scroll-step"> |
Latest revision as of 05:19, 21 December 2020
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