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

 
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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&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;--&nbsp;Overview</p>
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                                      <hr>
</br></br>
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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:</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.</br> </br>
 +
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>
 +
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>
 +
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 .
 +
</p>
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                                      <hr>
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      <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;">
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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.
 +
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.
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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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</p>
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<p style="border-bottom: 1px black solid ;font-size:25px;text-weight:bold;display:inline-block">What did our model achieve?</p>
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                                      <hr>
<p style="font-size:1.2em;">
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      <h1 style="font-size: 40px;font-weight: 900; padding-bottom: .7em">How did we model?</h1>
We achieved 3 main aims in our modelling work:
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<div class="col-md-push-1 col-md-10">
</br> We introduced a novel <a href="https://2016.igem.org/Team:Manchester/Model/ModelExplorer">ensemble modelling</a> approach to iGEM and made this approach accessible to other iGEM teams by sharing <a target="_Blank" href="https://github.com/Manchester-iGem-2016/Ensemble-Modelling">our code.</a>  
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<p alt="content_add" style="font-size: 18px;">
<br />
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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>
We improved our understanding of our system and used real experimental data to improve our model, using <a href="https://2016.igem.org/Team:Manchester/Model/MechanismUncertainty">network mechanism analysis </a> and <a href="https://2016.igem.org/Team:Manchester/Model/ParameterRelationships">parameter relationship analysis</a>. <br />
+
<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>
We answered key questions that arose during our <a href="https://2016.igem.org/Team:Manchester/Model/hp"> integrated human practices</a> work, helping to improve the design of our system using <a href="https://2016.igem.org/Team:Manchester/Model/Costing">cost analysis</a>.
+
<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.
 
+
</p>
 
+
</br></br>
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All of our models are available on <a target="_Blank" href="https://github.com/Manchester-iGem-2016/Ensemble-Modelling">our Github page</a>
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</div>
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<table>
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      <th><a href="https://2016.igem.org/Team:Manchester/Model/MechanismUncertainty">Network Mechanism Analysis </a></th>
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      <th><a href="https://2016.igem.org/Team:Manchester/Model/ParameterRelationships">Parameter Relationship Analysis</a></th>
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      <th><a href="https://2016.igem.org/Team:Manchester/Model/Costing">Cost Analysis</a></th>
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<tr>
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    <td>Comparing model predictions with experimental data for different potential circuit topologies. <a href="https://2016.igem.org/Team:Manchester/Model/MechanismUncertainty">read more</a></td>
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    <td>Assessing the interlinking nature of specific parameter pairings on the outcomes of the system. <a href="https://2016.igem.org/Team:Manchester/Model/ParameterRelationships"> read more </a></td>
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    <td>Predicting the costs for a range of different system specifications by varying the amount of enzymes based on experimental data. <a href="https://2016.igem.org/Team:Manchester/Model/Costing">read more</a></td>
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</tr>
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</table>
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<div class="modelling_info1">
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<p style="font-size:1.2em;">
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We found great inspiration from our <a href="https://2016.igem.org/Team:Manchester/Human_Practices/Industries">human practices</a> and guidance working both ways with the experiments. Click <a href="https://2016.igem.org/Team:Manchester/Model/hp"> here</a> to see a summary.
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</div>
 
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</div>
 
 
<div id="model1">
 
</div>
 
 
<div class="modelling_info1">
 
<p style="border-bottom: 1px black solid ;font-size:25px;text-weight:bold;display:inline-block">What were we modelling?</p>
 
<p style="font-size:1.2em;">
 
We focused on modelling the <a href="https://2016.igem.org/Team:Manchester/Description/mechanism1">Cell-free Mechanism</a>. The short version is the AlcoPatch relies on alcohol, alcohol oxidase (AOx), horseradish peroxidase (HRP) and 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulphonic acid) (ABTS) to detect and quantify alcohol levels. The ABTS<sub>Oxidised</sub> produced in the prescence of alcohol is dark green and can be detected spectophotometrically or visually.
 
</br></br>
 
We focused on this small system because it was possible to obtain a large amount of <a href="https://2016.igem.org/Team:Manchester/Notebook">experimental data</a> for model validation, and because it allowed us to establish and illustrate the <a href="https://2016.igem.org/Team:Manchester/Model/ModelExplorer">ensemble modelling</a> process.
 
</p>
 
<p style="font-size:1.2em;">
 
The majority of our experimental data came from the <a href="https://2016.igem.org/Team:Manchester/Proof">proof-of-concept</a> study of the analogous system of glucose and glucose oxidase (GOx) rather than alcohol and AOx. The reaction network of the two sytems is the same and only some kinetic parameters differ.
 
</p>
 
<p style="font-size:1.2em;">
 
A schematic diagram of the final circuit of our detection system is given below. </br>
 
<b> For more information about the individual reactions click on the blue enzyme boxes. </b>
 
</p>
 
<img class="full" src="https://static.igem.org/mediawiki/2016/0/04/T--Manchester--ModellingNetworkDiagram.png" alt="Reaction Network Diagram used in the modelling" usemap="#diagramclick" />
 
 
<map name="diagramclick">
 
<area shape="rect" coords="195,120,255,175" href="https://2016.igem.org/Team:Manchester/Model/GlucoseOxidaseReaction" title="Glucose Oxidase Reaction">
 
<area shape="rect" coords="505,155,566,210" href="https://2016.igem.org/Team:Manchester/Model/HorseRadishPeroxidaseReaction" title="HorseRadish Peroxidase Reaction">
 
</map>
 
 
</br>
 
<p style="font-size:1.2em;">
 
Alternatively you can click on the enzyme name below:
 
</p>
 
<p style="font-size:1.2em;">
 
<a href="https://2016.igem.org/Team:Manchester/Model/GlucoseOxidaseReaction">Glucose Oxidase</a>
 
</br>
 
<a href="https://2016.igem.org/Team:Manchester/Model/HorseRadishPeroxidaseReaction">Horseradish Peroxidase</a>
 
</p>
 
</div>
 
 
 
<div id="model2">
 
</div>
 
 
<div  class="modelling_info1">
 
<p style="border-bottom: 1px black solid ;font-size:25px;text-weight:bold;display:inline-block">What is Ensemble Modelling?</p>
 
<p style="font-size:1.2em;">
 
Incomplete and uncertain knowledge of kinetic parameters is a common problem when building models for synthetic biology. Ensemble modelling is one strategy to deal with this problem. Instead of running our model with a single set of specific parameters (for example rate constants), we run our model multiple times using different sets of plausible parameter values and analyse the predictions as an ensemble. We collected all the available parameter values from published literature and took into account the uncertainties that are associated with them. The resulting confidence in our parameter values was then described by <a href="https://2016.igem.org/Team:Manchester/Model/PDF">probability density functions</a>. </br>
 
 
This has created probabilistic outputs allowing us to make rigorous conclusions about our reaction mechanism – and to assess which predictions are reliable, and where we are lacking information. </br> </br>
 
 
<b>To explore the theory of this process please click the boxes on the diagram below.</b>
 
 
</p>
 
 
<img class="full" src="https://static.igem.org/mediawiki/2016/a/a9/T--Manchester--ModelFlowchart.jpg" alt="Overview flowchart of ensemble modelling" / usemap="#diagram1click">
 
 
 
 
<map name="diagram1click">
 
<area shape="rect" coords="70,82,413,190" href="https://2016.igem.org/Team:Manchester/Model/ParameterSelection" title="Parameter Selection">
 
<area shape="rect" coords="505,83,861,188" href="https://2016.igem.org/Team:Manchester/Model/PDF" title="PDF">
 
<area shape="rect" coords="635,305,850,411" href="https://2016.igem.org/Team:Manchester/Model/Simulate" title="system Simulate">
 
<area shape="rect" coords="338,307,553,412" href="https://2016.igem.org/Team:Manchester/Model/result" title="Result Analysis">
 
<area shape="rect" coords="50,298,265,400" href="https://2016.igem.org/Team:Manchester/Model/Story" title="Update Model">
 
</map>
 
 
 
 
<p style="font-size:1.2em;">
 
Alternatively you can click on the step name below:
 
</p>
 
<p  style="font-size:1.2em;">
 
 
<a href="https://2016.igem.org/Team:Manchester/Model/ParameterSelection">Collecting and Processing Data</a> </br>
 
<a href="https://2016.igem.org/Team:Manchester/Model/PDF">Generating Probability Density Functions</a> </br>
 
<a href="https://2016.igem.org/Team:Manchester/Model/Simulate">Simulate the System</a> </br>
 
<a href="https://2016.igem.org/Team:Manchester/Model/result">Analyse the Results</a> </br>
 
<a href="https://2016.igem.org/Team:Manchester/Model/Story">Story of the Model</a> </br>
 
</p>
 
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<a class="projectlink" href="https://2016.igem.org/Team:Manchester"><< Main Page</a>
 
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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.