Difference between revisions of "Team:UESTC-China/Model"

 
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<div class="bigtitle" id="title_1">Introduction</div>
 
<div class="bigtitle" id="title_1">Introduction</div>
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                <img src="https://static.igem.org/mediawiki/2019/d/d8/T--UESTC-China--model_new_1.png" alt="logo" width="70%">
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We combined modeling with experiments and human practice to make contributions to our project. For experiments, we established quorum sensing model and degradation optimization model. For human practice, we established the device layout model.
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Firstly, to understand the mechanism better and predict the results of the experiments, we modeled the quorum sensing mechanism from the microscopic point of view, which can help us find the optimal ratio of detection cells to processing cells. Undoubtedly, the model greatly saves the cost of our project.
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To further optimize our experiments, we investigated the external factors affecting the degradation of CIP by engineered bacteria from the macroscopic perspective. Through the reasonable experimental design, we can screen out the main influencing factors and obtain the response surface equation using PB design and Box-Behnken design. Finally, we will find the best external conditions, which improves the degradation rate of CIP.
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To make our device applied widely in real life, we established a device layout model from a more macroscopic perspective to provide a scientific solution for human practice and hardware. Therefore, the cost of our project is reduced and the efficiency of drug recovery is improved.
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  All in all, modeling is combined with experiments and human practice to make our project more integral.
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To further understand, predict, and control the behavior of engineered microbial quorum sensing, we modeled the quorum sensing based on the entire process of crpp enzyme production and degradation.
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To further understand, predict, and control the behavior of engineered microbial quorum sensing, we modeled the quorum sensing based on the entire process of CrpP enzyme's production and degradation.
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  The model involves a wide range of biological and physical processes, such as diffusion, binding and so on. Through the establishment and solution of differential equations, we have used this model to predict the relationship between the production of CrpP enzyme and the external concentration of AHL, which can help us find the optimal ratio of the detection bacteria to the degrading bacteria and save the cost of the device.  
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  The model involves a wide range of biological and physical processes, such as diffusion, binding and so on. Through the establishment and solution of differential equations, we have used this model to predict the connection between the production of CrpP enzyme and the concentration of external AHL, which can help us find the optimal ratio of the detection bacteria and the degrading bacteria in order to save the cost of the device by using a smaller number of engineered bacteria to achieve greater CrpP production.  
 
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<a href="https://2019.igem.org/Team:UESTC-China/Model1" class="myclick">please click here to read more</a>
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<a href="https://2019.igem.org/Team:UESTC-China/Model1" class="myclick">please click here to read the wiki of this model</a>
 
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In order to find the optimal degradation conditions for CrpP enzyme, we found the factors affecting the degradation rate from the paper.
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To further optimize our experiments, we found the factors affecting the degradation rate from papers. We designed a scheme which used the Plackett-Burman design to screen factors. We can get the key factors through experiments in the future. The Box-Behnken design will be used in the experimental design. According to the future experimental results, the response surface equation can be obtained. Then, we can find the optimal external influence factors (eg. PH, temperature) and increase the degradation rate to optimize our experiment. At present, we are working hard to get the experimental data. In the future, we will use our scheme to optimize our experiment and adjust our model with experimental data.
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We designed a scheme which uses the Plackett-Burman design to screen factors and get the important factors. The Box-Behnken design will be used in the experimental design. According to the future experimental results, the response surface equation can be obtained. Then, we can find the optimal external influence factors and increase the degradation rate to optimize our experiment. At present, we are working hard to get the experimental data. In the future, we will use our scheme to optimize our experiment and adjust our model with experimental data.
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                 <a href="https://2019.igem.org/Team:UESTC-China/Model2" class="myclick">please click here to read more</a>
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                 <a href="https://2019.igem.org/Team:UESTC-China/Model2" class="myclick">please click here to read the wiki of this model</a>
 
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<p>We combined modeling with human practice and established the layout model of devices to provide a solution for human practice. Inspired by the placement of dustbins now, firstly we carried out the layout of the dustbin by using the multi-objective programming model, and then carried out the layout of the device. Finally, we made the dustbin and the device as close as possible to increase the probability of residents throwing expired drugs. The model reduced costs of our project and increased the efficiency of processing expired drugs.</p>
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<p>We combined modeling with human practice and established the layout model of devices to provide a solution for human practice. As we all know, for convenience, people hope to discard expired drugs while discarding garbage. So placing the device and the trash can as close as possible can increase the possibility of drugs recycling. Due to the expect that changing current situation of unscientific placement of trash cans, we carried out the layout of the trash cans by using the multi-objective programming model, and then worked out the layout of the device. Finally, we achieved our goal to use a minimum number of devices but the highest efficiency of drugs recycling.</p>
             <a href="https://2019.igem.org/Team:UESTC-China/Model3" class="myclick">please click here to read more</a>
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             <a href="https://2019.igem.org/Team:UESTC-China/Model3" class="myclick">please click here to read the wiki of this model</a>
 
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Latest revision as of 01:17, 22 October 2019

description

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Introduction
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We combined modeling with experiments and human practice to make contributions to our project. For experiments, we established quorum sensing model and degradation optimization model. For human practice, we established the device layout model.

Quorum sensing model
To further understand, predict, and control the behavior of engineered microbial quorum sensing, we modeled the quorum sensing based on the entire process of CrpP enzyme's production and degradation.

The model involves a wide range of biological and physical processes, such as diffusion, binding and so on. Through the establishment and solution of differential equations, we have used this model to predict the connection between the production of CrpP enzyme and the concentration of external AHL, which can help us find the optimal ratio of the detection bacteria and the degrading bacteria in order to save the cost of the device by using a smaller number of engineered bacteria to achieve greater CrpP production.
Degradation optimization model
To further optimize our experiments, we found the factors affecting the degradation rate from papers. We designed a scheme which used the Plackett-Burman design to screen factors. We can get the key factors through experiments in the future. The Box-Behnken design will be used in the experimental design. According to the future experimental results, the response surface equation can be obtained. Then, we can find the optimal external influence factors (eg. PH, temperature) and increase the degradation rate to optimize our experiment. At present, we are working hard to get the experimental data. In the future, we will use our scheme to optimize our experiment and adjust our model with experimental data.
Device layout optimization model

We combined modeling with human practice and established the layout model of devices to provide a solution for human practice. As we all know, for convenience, people hope to discard expired drugs while discarding garbage. So placing the device and the trash can as close as possible can increase the possibility of drugs recycling. Due to the expect that changing current situation of unscientific placement of trash cans, we carried out the layout of the trash cans by using the multi-objective programming model, and then worked out the layout of the device. Finally, we achieved our goal to use a minimum number of devices but the highest efficiency of drugs recycling.

please click here to read the wiki of this model
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