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

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<li><a href="https://2017.igem.org/Team:XMU-China/Demonstrate">Demonstrate</a></li>
 
<li><a href="https://2017.igem.org/Team:XMU-China/Demonstrate">Demonstrate</a></li>
 
<li><a href="https://2017.igem.org/Team:XMU-China/Results">Results</a></li>
 
<li><a href="https://2017.igem.org/Team:XMU-China/Results">Results</a></li>
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<li><a href="https://2017.igem.org/Team:XMU-China/Measurement">Measurement</a></li>
 
<li><a href="https://2017.igem.org/Team:XMU-China/Parts">Parts</a></li>
 
<li><a href="https://2017.igem.org/Team:XMU-China/Parts">Parts</a></li>
 
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<li><a href="https://2017.igem.org/Team:XMU-China/Model">Overview</a></li>
 
<li><a href="https://2017.igem.org/Team:XMU-China/Model">Overview</a></li>
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<li><a href="https://2017.igem.org/Team:XMU-China/Model_Description">Description</a></li>
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<li><a href="https://2017.igem.org/Team:XMU-China/Model_Method">Method</a></li>
 
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<li><a href="https://2017.igem.org/Team:XMU-China/Engagement">Engagement</a></li>
 
<li><a href="https://2017.igem.org/Team:XMU-China/Engagement">Engagement</a></li>
 
<li><a href="https://2017.igem.org/Team:XMU-China/Entrepreneurship">Entrepreneurship</a></li>
 
<li><a href="https://2017.igem.org/Team:XMU-China/Entrepreneurship">Entrepreneurship</a></li>
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<li><a href="https://2017.igem.org/Team:XMU-China/HP/Newsletter">Newsletter</a></li>
 
 
<li><a href="https://2017.igem.org/Team:XMU-China/Collaborations">Collaborations</a></li>
 
<li><a href="https://2017.igem.org/Team:XMU-China/Collaborations">Collaborations</a></li>
 
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<p>Quantitative analysis of the dynamics in cellular systems is a key aspect of synthetic biology and engineering with the tool of the mathematical model, which not only integrates gene expression data, but also provides an important approach to understanding the dynamics by quantifying the interaction between the regulatory components. At present, the mainstream methods of modeling control network include Petri net, Bayesian network and differential equation model.<br /><br />
 
<p>Quantitative analysis of the dynamics in cellular systems is a key aspect of synthetic biology and engineering with the tool of the mathematical model, which not only integrates gene expression data, but also provides an important approach to understanding the dynamics by quantifying the interaction between the regulatory components. At present, the mainstream methods of modeling control network include Petri net, Bayesian network and differential equation model.<br /><br />
 
In our project, the main idea is to construct certain kinds of recombinant plasmids by selecting the corresponding metal-sensitive promoters binding with the reporter genes with T7 amplification systems to decrease the detection limit. It is fairly essential to get the accuracy of experimental data since the experiment of detecting the amount of signals which is transferred as detectable, is based on gene circuit, where lays the purport of mathematical modeling.<br /><br />
 
In our project, the main idea is to construct certain kinds of recombinant plasmids by selecting the corresponding metal-sensitive promoters binding with the reporter genes with T7 amplification systems to decrease the detection limit. It is fairly essential to get the accuracy of experimental data since the experiment of detecting the amount of signals which is transferred as detectable, is based on gene circuit, where lays the purport of mathematical modeling.<br /><br />
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Our models can be divided into two different aspects. On gene level, we hope to the confirm that metal ion concentration is positively correlated with the promoter activity, also we hope to gain insight of the gene expression dynamics of our whole circuit using the differential equation model. On the aspect of human practices, we manage to sum up the rate of change of pollutants by Grossman Model.
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Our models can be divided into two different aspects. On gene level, we hope to the confirm that metal ion concentration is positively correlated with the promoter activity, also we hope to gain insight of the gene expression dynamics of our whole circuit using the differential equation model. On the aspect of human practices, we manage to investigate the relationship between environmental pollutants and economic, and chose Grossman model to explore the relationship and the amount of GDP emission environment.
 
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Revision as of 10:09, 27 October 2017

2017.igem.org/Team:XMU-China/Model

Overview

Quantitative analysis of the dynamics in cellular systems is a key aspect of synthetic biology and engineering with the tool of the mathematical model, which not only integrates gene expression data, but also provides an important approach to understanding the dynamics by quantifying the interaction between the regulatory components. At present, the mainstream methods of modeling control network include Petri net, Bayesian network and differential equation model.

In our project, the main idea is to construct certain kinds of recombinant plasmids by selecting the corresponding metal-sensitive promoters binding with the reporter genes with T7 amplification systems to decrease the detection limit. It is fairly essential to get the accuracy of experimental data since the experiment of detecting the amount of signals which is transferred as detectable, is based on gene circuit, where lays the purport of mathematical modeling.

Our models can be divided into two different aspects. On gene level, we hope to the confirm that metal ion concentration is positively correlated with the promoter activity, also we hope to gain insight of the gene expression dynamics of our whole circuit using the differential equation model. On the aspect of human practices, we manage to investigate the relationship between environmental pollutants and economic, and chose Grossman model to explore the relationship and the amount of GDP emission environment.