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

 
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                     &#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 Danteeth, including quorum sensing, target peptide expression. Altogether, the model enables Danteeth to optimize continually with the help of reinforcement AI. The model consists of two parts:
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                     &#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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                         <li><a href="https://2021.igem.org/Team:NCTU_Formosa/Prediction_Model">Prediction Model(Click to this  
 
                         <li><a href="https://2021.igem.org/Team:NCTU_Formosa/Prediction_Model">Prediction Model(Click to this  
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                     <img class="ReadMore2" id="img_Close" src="https://static.igem.org/mediawiki/2021/5/50/T--NCTU_Formosa--close.svg">*/
 
                     <img class="ReadMore2" id="img_Close" src="https://static.igem.org/mediawiki/2021/5/50/T--NCTU_Formosa--close.svg">*/
 
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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">
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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>
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                </svg>The structure of the model</div>
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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>
 
                     <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>
 
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                 </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">
 
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                     <h1 class="subtopic">Efficiency Optimization Model</h1>
 
                     <h1 class="subtopic">Efficiency Optimization Model</h1>

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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