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

 
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<title>2017.igem.org/Team:XMU-China/Model</title>
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Model
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<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 <strong>Petri net, Bayesian network and differential equation model.</strong><br /><br />
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In our project, the main idea is to construct certain kinds of recombinant plasmids by selecting the corresponding pollutant ion sensing promoters binding with the reporter genes with T7 amplification systems to <strong>decrease the detection limit.</strong> It is fairly essential to get the accuracy of experimental data since the experiment of detecting the intensity of signals which is transferred as detectable, is based on the gene circuit, where lays the purport of mathematical modeling.<br /><br />
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Our models can be divided into three different aspects. On the <a href="https://2017.igem.org/Team:XMU-China/Modeling">gene level</a>, we hope to confirm that the concentration of pollutant ions is positively correlated with the promoter activity. And also we hope to gain insight of the gene expression dynamics of our whole circuit using <strong>the differential equation model</strong>. Furthermore, we have made a series of regression models about luxAB and tried to explain the surival of freeze dried bacteria with <strong>the Boyle van't Hoff relationship</strong>. On the aspect of <a href="https://2017.igem.org/Team:XMU-China/HP/Gold_Integrated">human practices</a>, we manage to investigate the relationship between environmental pollutants and economic, and choose <strong>Grossman model</strong> to explore the relationship and the amount of GDP emission environment. </p>
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        <p>The team's project description must be documented on their iGEM Team Wiki by the deadline. The project description should be 1-3 paragraphs and only needs to include an up-to-date explanation of the project. This description should be posted on your Team Wiki home page (example URL: https://2017.igem.org/Team:Example).This description will not be used to judge your project. It serves to provide some background on what your team has been working on so far and what you hope to accomplish. It also provides other teams the opportunity to see what you're working on so they can reach out for collaborations or troubleshooting if they are exploring a similar topic. </p>
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        <p>Once the wikis are frozen, users can no longer make any changes until they are unfrozen after the Jamboree. Please be sure to read through the the wiki requirements! No extensions will be provided (no exceptions!) and judges will begin their assessment on November 2, so make sure all changes are done by 11:59PM EDT.PLEASE NOTE: During week of wiki freeze, iGEM experiences higher than normal traffic which can lead to strain on our servers and sessions timing out for users. iGEM HQ recommends that users do not wait till the last days to work on and/or finish their wikis. Edits done during the final week should be very minor edits (spelling mistakes, updating images, etc.). </p>
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<p>Xiamen University，Fujian,China</p>
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<p>Xiamen University, Fujian, China<br />
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<p>No. 422, Siming South Road, Xiamen, Fujian, P. R. China 361005</p>
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No. 422, Siming South Road, Xiamen, Fujian, P. R. China 361005</p>
 
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Latest revision as of 16:34, 1 November 2017

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


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 pollutant ion sensing 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 intensity of signals which is transferred as detectable, is based on the gene circuit, where lays the purport of mathematical modeling.

Our models can be divided into three different aspects. On the gene level, we hope to confirm that the concentration of pollutant ions is positively correlated with the promoter activity. And also we hope to gain insight of the gene expression dynamics of our whole circuit using the differential equation model. Furthermore, we have made a series of regression models about luxAB and tried to explain the surival of freeze dried bacteria with the Boyle van't Hoff relationship. On the aspect of human practices, we manage to investigate the relationship between environmental pollutants and economic, and choose Grossman model to explore the relationship and the amount of GDP emission environment.