Difference between revisions of "Team:NCTU Formosa/Model"

 
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         </div>
 
         </div>
 
         <div class="main-content">
 
         <div class="main-content">
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             <img src="https://static.igem.org/mediawiki/2021/0/02/T--NCTU_Formosa--next.png" id="nextBottom" />
 
             <div class="section s2">
 
             <div class="section s2">
 
                 <h1 class="topic" id="topic2">Overview</h1>
 
                 <h1 class="topic" id="topic2">Overview</h1>
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                 <p id="p1">
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                 <!--<p id="p1">
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                     &#8195;&#8195;Modeling is calculating the physical phenomenon by using mathematical methods or logical algorithms.
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                     &#8195;&#8195;Modeling is calculating the physical phenomenon by using mathematical methods or logical algorithms.<br><br><br>-->
 
                 </p>
 
                 </p>
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                 <p id="p2" style="display:none;">
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                 <p id="p2" >
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                     &#8195;&#8195;Our model aims at making the DenTeeth work precisely and optimizing the efficiency of this product. First, the Prediction Model predicts the bacterial growth curve and the expression of protein and peptide with a quorum sensing system. Second, by developing a reinforcement learning AI which can accurately find out the best frequency for each dog using DenTeeth by the results of the Prediction Model. Our model can be divided into the following two parts:
+
                     &#8195;&#8195;Oral cavity is a hotbed for pathogens of periodontal diseases, as the goal of modelling is to simulate the microenvironment incorporated with Denteeth, mainly the overturn of pathogens, and make predictions on their extinction. Therefore, we compute the competing bacterial growing patterns, and the killing effect on pathogens. Also, we propose a renew rate of the final product, considering the biobrick design in DenTeeth, including quorum sensing, target peptide expression. Altogether, the model enables DenTeeth to optimize continually with the help of reinforcement AI. The model consists of two parts:
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                     <ol id="list" style="display:none;">
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                     <ol id="list" >
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                         <li>Prediction Model</li>
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                         <li><a href="https://2021.igem.org/Team:NCTU_Formosa/Prediction_Model">Prediction Model(Click to this
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                         <li>Optimized Frequency Model</li>
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                            page)</a></li>
 +
                         <li><a href="https://2021.igem.org/Team:NCTU_Formosa/Efficiency_Optimization_Model">Efficiency
 +
                              Optimization Model(Click to this page)</a></li>
 
                     </ol>
 
                     </ol>
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                 </p>
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                 </p><!--
 
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                 </div>-->
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             </div>          
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                <img src="https://static.igem.org/mediawiki/2021/2/26/T--NCTU_Formosa--rainnie_model_flow_chart.png?fbclid=IwAR0BygOOr-lu6uy3B2_jgEBJJL4l8N97nVDCRqj4ETNPZRjBqbU7NAFakiQ" class="images" id=" Growth_PE" alt=" growth curve of E. coli and P.gingivalis"/>
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                <div class="explanation"><svg class="icon" aria-hidden="true" data-prefix="fas" data-icon="arrow-circle-up"
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                    role="img" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512">
 +
                    <path fill="currentColor"
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                        d="M8 256C8 119 119 8 256 8s248 111 248 248-111 248-248 248S8 393 8 256zm143.6 28.9l72.4-75.5V392c0 13.3 10.7 24 24 24h16c13.3 0 24-10.7 24-24V209.4l72.4 75.5c9.3 9.7 24.8 9.9 34.3.4l10.9-11c9.4-9.4 9.4-24.6 0-33.9L273 107.7c-9.4-9.4-24.6-9.4-33.9 0L106.3 240.4c-9.4 9.4-9.4 24.6 0 33.9l10.9 11c9.6 9.5 25.1 9.3 34.4-.4z">
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                    </path>
 +
                </svg>The structure of the model</div>
 +
                </div>
 +
 
 +
             </div>      
 
             <div class="dog-button">
 
             <div class="dog-button">
 
                 <div class="dog-img" id="img-link1">
 
                 <div class="dog-img" id="img-link1">
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                 </div>
 
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                 <div class="dog-img" id="img-link2">
 
                 <div class="dog-img" id="img-link2">
−
                     <div class="dog-txt-c">Optimized Frequency Model</div>
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                     <div class="dog-txt-c">Efficiency Optimization Model</div>
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                     <img src="https://static.igem.org/mediawiki/2021/8/8a/T--NCTU_Formosa--quorum_link.svg" title="Edward Jenner" alt="Design">
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                     <img style="border-radius: 0 5% 0 0;" src="https://static.igem.org/mediawiki/2021/8/8a/T--NCTU_Formosa--quorum_link.svg" title="Edward Jenner" alt="Design">
 
                 </div>
 
                 </div>
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                <div class="dog-img" id="img-link3">
 
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                    <div class="dog-txt-up">Hardware</div>
 
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                    <img style="border-radius: 0 5% 0 0;" src="https://static.igem.org/mediawiki/2021/f/f6/T--NCTU_Formosa--optimized_freq_link.svg" title="fauxels" alt="hp">
 
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                 <div id="tab01" class="tab-inner" style="display:block;">
 
                 <div id="tab01" class="tab-inner" style="display:block;">
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                     &#8195;&#8195;The Prediction Model is mainly to analyze the growth of bacteria and the expression of protein and peptide. It can also predict the killing rate and sterilization rate. By this model, we can define the efficiency of DenTeeth.
 
                     &#8195;&#8195;The Prediction Model is mainly to analyze the growth of bacteria and the expression of protein and peptide. It can also predict the killing rate and sterilization rate. By this model, we can define the efficiency of DenTeeth.
 
                     </p>
 
                     </p>
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                     <a href="https://2021.igem.org/Team:NCTU_Formosa/Growth_model"><img class="ReadMore1" src="https://static.igem.org/mediawiki/2021/2/22/T--NCTU_Formosa--double-chevron.svg"></a>
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                     <a href="https://2021.igem.org/Team:NCTU_Formosa/Prediction_Model"><img class="ReadMore1" src="https://static.igem.org/mediawiki/2021/2/22/T--NCTU_Formosa--double-chevron.svg"></a>
 
                 </div>
 
                 </div>
 
                 <div id="tab02" class="tab-inner">
 
                 <div id="tab02" class="tab-inner">
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                     <h1 class="subtopic">Optimized Frequency Model</h1>
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                     <h1 class="subtopic">Efficiency Optimization Model</h1>
 
                     <p>
 
                     <p>
 
                     &#8195;&#8195;To optimize the frequency of using DenTeeth and making our model applies to the dogs better. We input the results of the Prediction Mode to the Optimized Frequence Model and find out the best strategy.
 
                     &#8195;&#8195;To optimize the frequency of using DenTeeth and making our model applies to the dogs better. We input the results of the Prediction Mode to the Optimized Frequence Model and find out the best strategy.
 
                     </p>
 
                     </p>
−
                     <a href="https://2021.igem.org/Team:NCTU_Formosa/Quorum_Sensing_Model"><img class="ReadMore1" src="https://static.igem.org/mediawiki/2021/2/22/T--NCTU_Formosa--double-chevron.svg"></a>
+
                     <a href="https://2021.igem.org/Team:NCTU_Formosa/Efficiency_Optimization_Model"><img class="ReadMore1" src="https://static.igem.org/mediawiki/2021/2/22/T--NCTU_Formosa--double-chevron.svg"></a>
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                </div>
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                <div id="tab03" class="tab-inner">
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                    <h1 class="subtopic">Hardware</h1>
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                    <p>
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                    &#8195;&#8195;思考中...
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                    </p>
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                    <a href="https://2021.igem.org/Team:NCTU_Formosa/Optimized_Frequency_Model"><img class="ReadMore1" src="https://static.igem.org/mediawiki/2021/2/22/T--NCTU_Formosa--double-chevron.svg"></a>
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                 </div>
 
                 </div>
  
 
             <div style="position: relative;">
 
             <div style="position: relative;">
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         </div>
 
         </div>
 +
<div id="dark_mode"><span class="material-icons">
 +
dark_mode
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</span>Dark Mode</div>
 
     </main>
 
     </main>
 
</body>
 
</body>
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Latest revision as of 15:30, 30 November 2021


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Overview

  Oral cavity is a hotbed for pathogens of periodontal diseases, as the goal of modelling is to simulate the microenvironment incorporated with Denteeth, mainly the overturn of pathogens, and make predictions on their extinction. Therefore, we compute the competing bacterial growing patterns, and the killing effect on pathogens. Also, we propose a renew rate of the final product, considering the biobrick design in DenTeeth, including quorum sensing, target peptide expression. Altogether, the model enables DenTeeth to optimize continually with the help of reinforcement AI. The model consists of two parts:

  1. Prediction Model(Click to this page)
  2. Efficiency Optimization Model(Click to this page)

growth curve of E. coli and P.gingivalis
The structure of the model
Prediction Model
dog
Efficiency Optimization Model
Design

Prediction Model

  The Prediction Model is mainly to analyze the growth of bacteria and the expression of protein and peptide. It can also predict the killing rate and sterilization rate. By this model, we can define the efficiency of DenTeeth.

Efficiency Optimization Model

  To optimize the frequency of using DenTeeth and making our model applies to the dogs better. We input the results of the Prediction Mode to the Optimized Frequence Model and find out the best strategy.

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