Difference between revisions of "Team:NUDT CHINA/Model/Overview"

 
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   <p style="font-size:36px;margin: 0 0%;padding: 8% 0 0 10%;color: white;">Designed Protein Degradation Method Based on</p>
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   <p style="font-size:36px;margin: 0 0%;padding: 5% 0 0 10%;color: white;">Designed Protein Degradation Method Based on</p>
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<p style="font-size:36px;margin: 0 0%;padding: 0 0 0 10%;color: white;">Trim21 And Nanobody</p>
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<p style="font-size:36px;margin: 0 0%;padding: 0 0 0 10%;color: white;">Trim21 And Nanobody&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;--&nbsp;Overview</p>
 
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                                   <a href="#model1"><img src="https://static.igem.org/mediawiki/2016/c/c1/T--Manchester--modelling1_pic.png" style="width:100%" alt="What were we modelling?"></img></a>
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                                   <a href="#model1"><img src="https://static.igem.org/mediawiki/2018/9/9c/T--NUDT_CHINA--acheive1.gif" style="width:100%" alt="What were we modelling?"></img></a>
 
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                                   <a href="#model2"><img src="https://static.igem.org/mediawiki/2018/c/cf/T--NUDT_CHINA--what1.gif" style="width:100%" alt="How were we modelling?"></img></a>
 
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                                   <a href="#model3"><img src="https://static.igem.org/mediawiki/2016/4/46/T--Manchester--modelling3_pic.png" style="width:100%" alt="What does our modelling achieve?"></img></a>
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                                   <a href="#model3"><img src="https://static.igem.org/mediawiki/2018/f/fc/T--NUDT_CHINA--how2.gif" style="width:100%" alt="What does our modelling achieve?"></img></a>
 
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      <h1 style="font-size: 40px;font-weight: 900; padding-bottom: .7em">What does our modelling achieve?</h1>
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      <h1 style="font-size: 40px;font-weight: 900; padding-bottom: .7em">What did our model achieve?</h1>
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We achieved 4 main aims in our modelling work:  
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We achieved 4 main aims in our modelling work:</br>
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1、We simulated the whole process from plasmid introduction to protein degradation,which deepens our understanding of reaction mechanism. The real experimental data is also used to improve our model, with the help of network mechanism analysis and parameter relationship analysis.
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1、We simulated the whole process from plasmid introduction to protein degradation,which deepens our understanding of reaction mechanism. The real experimental data is also used to improve our model, with the help of network mechanism analysis and parameter relationship analysis.</br> </br>
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2、We continued to follow the parameters simulation method of Team William and Mary used in the last iGEM and provide insights for other teams who want to use this approach.  
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2、We used both <a href=" https://2018.igem.org/Team:NUDT_CHINA/Model/Basic_Design">least squares and neural networks</a> to analyze the data and obtain the relationship between protein degradation and plasmid concentration,the use of which two methods makes the entire construction more reliable and provide insights for other teams who want to use this approach. </br> </br>
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3、We offered some suggestions to wetlab according to sensitivity analysis，helping them to find the reason on how different factors work.
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3、We offered some suggestions to wetlab according to <a href=" https://2018.igem.org/Team:NUDT_CHINA/Model/Deduction">sensitivity analysis</a>,helping them to find the reason on how different factors work.</br> </br>
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4、We detected the appropriate check point to find the time of protein degradation to a certain proportion.By this means,we could offer advices on the amount of plasmid introduction， combined with（病人对降解时间和蛋白平衡浓度的需要）during future clinical practice .  
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4、We detected the appropriate check point to find the time of protein degradation to a certain proportion.By this means,we could offer advice on the amount of plasmid introduction, combined with patients’needs to protein degradation time and concentration of protein at equilibrium during future practice .  
 
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      <h1 style="font-size: 40px;font-weight: 900; padding-bottom: .7em">What were we modelling?</h1>
 
      <h1 style="font-size: 40px;font-weight: 900; padding-bottom: .7em">What were we modelling?</h1>
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<p alt="content_add" style="font-size: 18px;">对模型进行描述</p>
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We focused on building ODE models to describe the whole process from plasmid introduction to protein degradation ，predicting different XXX（加句话将蛋白质和表现型联系起来，“从而预测实验时会观察到的不同现象）
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We focused on building ODE models to describe the whole process from plasmid introduction to protein degradation ,predicting different circumstances observed in wetlab.
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Based on these minds，we model two different antibodies GFP and ErbB3 respectively.  
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Based on these minds,we model two different antibodies <a href=" https://2018.igem.org/Team:NUDT_CHINA/Model/Deduction">GFP and ErbB3</a> respectively.  
 
We simulated the two process of introducing plasmids carrying different antibodies （GFP and ErbB3）into cells respectively.
 
We simulated the two process of introducing plasmids carrying different antibodies （GFP and ErbB3）into cells respectively.
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The majority of our experimental data came from the proof-of-concept study of the GFP system，as the reaction network of the two sytems is the same and only some kinetic parameters differ.
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The majority of our experimental data came from the proof-of-concept study of the GFP system,as the reaction network of the two systems is the same and only some kinetic parameters differ.
 
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Model parameterization: we modeled the whole process of our system to mathematize the process, using kinetic and dynamic models solved by analytical and numerical simulation techniques.（Law of mass action ，antigen-antibody reaction kinetics and our own equations ）
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<a href="https://2018.igem.org/Team:NUDT_CHINA/Model/Basic_Design">Model parameterization</a>: we modeled the whole process of our system to mathematize the process, using kinetic and dynamic models solved by analytical and numerical simulation techniques.（Law of mass action ,antigen-antibody reaction kinetics and our own equations ）</br></br>
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Computer assistance：we use Simbiology for solving differential equations, data visualization, sensitivity analysis, range scanning（这个好像不是这么表达的） and comparison with existing data to verify the accuracy of the model
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<a href="https://2018.igem.org/Team:NUDT_CHINA/Model/Basic_Design">Computer assistance</a>:we used Simbiology for solving differential equations, data visualization, sensitivity analysis, parameter sweeps and comparison with existing data to verify the accuracy of the model.</br></br>
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Parameters simulation:
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<a href=" https://2018.igem.org/Team:NUDT_CHINA/Model/Basic_Design">Data analysis</a>:we used both least squares and neural networks to analyze the data and obtain the relationship between protein degradation and plasmid concentration,the use of which two methods makes the entire construction more reliable.
 
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Example block-level help text here.There are several variants of  derived from different organisms. In our project, we  . The structure of this protein has been determined with and without  The  a  lobe. The two lobes are positively charged towards the protein core to accommodate the negatively charged RNA. Each of these two lobes contains an RNase domain. At the  main is responsible for target cleavage. In contrast to other  two RNase domains of the NUC lobe are located at the outside of the protein, which is likely the reason collateral cleavage upon activation by binding to a matching target. These two domains have been labeled as red spots in Figure 2 and can be found at the interface between the green and pink domain.
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Latest revision as of 02:01, 18 October 2018

Designed Protein Degradation Method Based on

Trim21 And Nanobody              -- Overview

What were we modelling?
How were we modelling?
What does our modelling achieve?

What did our model achieve?

We achieved 4 main aims in our modelling work:
1、We simulated the whole process from plasmid introduction to protein degradation,which deepens our understanding of reaction mechanism. The real experimental data is also used to improve our model, with the help of network mechanism analysis and parameter relationship analysis.

2、We used both least squares and neural networks to analyze the data and obtain the relationship between protein degradation and plasmid concentration,the use of which two methods makes the entire construction more reliable and provide insights for other teams who want to use this approach.

3、We offered some suggestions to wetlab according to sensitivity analysis,helping them to find the reason on how different factors work.

4、We detected the appropriate check point to find the time of protein degradation to a certain proportion.By this means,we could offer advice on the amount of plasmid introduction, combined with patients’needs to protein degradation time and concentration of protein at equilibrium during future practice .

What were we modelling?

We focused on building ODE models to describe the whole process from plasmid introduction to protein degradation ,predicting different circumstances observed in wetlab. Based on these minds,we model two different antibodies GFP and ErbB3 respectively. We simulated the two process of introducing plasmids carrying different antibodies （GFP and ErbB3）into cells respectively. The majority of our experimental data came from the proof-of-concept study of the GFP system,as the reaction network of the two systems is the same and only some kinetic parameters differ.

How did we model?

Model parameterization: we modeled the whole process of our system to mathematize the process, using kinetic and dynamic models solved by analytical and numerical simulation techniques.（Law of mass action ,antigen-antibody reaction kinetics and our own equations ）

Computer assistance:we used Simbiology for solving differential equations, data visualization, sensitivity analysis, parameter sweeps and comparison with existing data to verify the accuracy of the model.

Data analysis:we used both least squares and neural networks to analyze the data and obtain the relationship between protein degradation and plasmid concentration,the use of which two methods makes the entire construction more reliable.