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<div class="section s2"> | <div class="section s2"> | ||
<h1 class="topic" id="topic2">Overview</h1> | <h1 class="topic" id="topic2">Overview</h1> | ||
− | <p id="p1"> | + | <!--<p id="p1"> |
− |   Modeling is calculating the physical phenomenon by using mathematical methods or logical algorithms.<br><br><br> | + |   Modeling is calculating the physical phenomenon by using mathematical methods or logical algorithms.<br><br><br>--> |
</p> | </p> | ||
− | <p id="p2 | + | <p id="p2" > |
− |   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 | + |   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: |
− | <ol id="list | + | <ol id="list" > |
− | <li>Prediction Model</li> | + | <li><a href="https://2021.igem.org/Team:NCTU_Formosa/Prediction_Model">Prediction Model(Click to this |
− | <li>Efficiency Optimization Model</li> | + | 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> | ||
− | </p> | + | </p><!-- |
<div id="Btn_Open"> | <div id="Btn_Open"> | ||
− | <img class="ReadMore2" id="img_Open" src="https://static.igem.org/mediawiki/2021/1/15/T--NCTU_Formosa--ellipsis.svg"> | + | <img class="ReadMore2" style="display: none; " id="img_Open" src="https://static.igem.org/mediawiki/2021/1/15/T--NCTU_Formosa--ellipsis.svg"> |
</div> | </div> | ||
<div id="Btn_Close"> | <div id="Btn_Close"> | ||
− | <img class="ReadMore2 | + | <img class="ReadMore2" id="img_Close" src="https://static.igem.org/mediawiki/2021/5/50/T--NCTU_Formosa--close.svg">*/ |
− | </div> | + | </div>--> |
+ | <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"/> | ||
+ | <div class="explanation"><svg class="icon" aria-hidden="true" data-prefix="fas" data-icon="arrow-circle-up" | ||
+ | role="img" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"> | ||
+ | <path fill="currentColor" | ||
+ | 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"> | ||
+ | </path> | ||
+ | </svg>The structure of the model</div> | ||
+ | </div> | ||
+ | |||
</div> | </div> | ||
<div class="dog-button"> | <div class="dog-button"> | ||
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margin-bottom: 10%; | margin-bottom: 10%; | ||
margin-top: 5%; | margin-top: 5%; | ||
− | border-width: 5px; | + | /*border-width: 5px; |
border-style: dashed; | border-style: dashed; | ||
− | border-color: rgb(255, 193, 7); | + | border-color: rgb(255, 193, 7);*/ |
} | } | ||
.s2 p{ | .s2 p{ | ||
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.dog-button { | .dog-button { | ||
display: flex; | display: flex; | ||
− | width: | + | width: 80%; |
justify-content: space-between; | justify-content: space-between; | ||
justify-content: center; | justify-content: center; | ||
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} | } | ||
.tab-inner{ | .tab-inner{ | ||
− | width: | + | width: 80%; |
height: 400px; | height: 400px; | ||
background-color: #1d4eac; | background-color: #1d4eac; | ||
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display: none; | display: none; | ||
position: relative; | position: relative; | ||
+ | margin-left: auto; | ||
+ | margin-right: auto; | ||
} | } | ||
.ReadMore1{ | .ReadMore1{ | ||
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cursor: pointer; | cursor: pointer; | ||
} | } | ||
− | #list li{ | + | #list li a{ |
font-size: 2vw !important; | font-size: 2vw !important; | ||
} | } | ||
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padding-left: 5% !important; | padding-left: 5% !important; | ||
font-size: 2vw !important; | font-size: 2vw !important; | ||
− | padding-bottom: | + | padding-bottom: 5%; |
} | } | ||
.night{ | .night{ | ||
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color: RGB(253,172,83); | color: RGB(253,172,83); | ||
} | } | ||
+ | .explanation { | ||
+ | font-size: 1.3vw; | ||
+ | text-align: center; | ||
+ | margin: 10px 0 10%; | ||
+ | color: RGB(253, 172, 83); | ||
+ | } | ||
+ | .explanation i{ | ||
+ | font-size: 1.3vw; | ||
+ | } | ||
+ | .icon { | ||
+ | width: 1.5vw; | ||
+ | color: RGB(253, 172, 83); | ||
+ | } | ||
@media screen and (max-width: 750px){ | @media screen and (max-width: 750px){ | ||
#nextBottom{ | #nextBottom{ | ||
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font-size: 5vw !important; | font-size: 5vw !important; | ||
} | } | ||
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line-height: 50px; | line-height: 50px; | ||
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} | } | ||
#list{ | #list{ | ||
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+ | } | ||
+ | .explanation { | ||
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+ | } | ||
+ | .explanation i{ | ||
+ | font-size: 2vw; | ||
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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:
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.