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

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         <img src="https://static.igem.org/mediawiki/2018/a/a1/T--ASTWS-China--Model1.png">
 
         <img src="https://static.igem.org/mediawiki/2018/a/a1/T--ASTWS-China--Model1.png">
 
         <p>Based on a common knowledge, both time and concentration will affect the bacterium’s growth, we had the first empirical equation, the two-variable linear function is then applied to test the simulation of these real-world data.</p>
 
         <p>Based on a common knowledge, both time and concentration will affect the bacterium’s growth, we had the first empirical equation, the two-variable linear function is then applied to test the simulation of these real-world data.</p>
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         <p>E = a &#215; C + b &#215; H + d (a, b, d are constants)</p>
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        <p>By the regression in the Matlab, we have obtained the function of E = 17.4 &#215; C + 68.23 &#215; H + 1181 where R<sup>2</sup> = 0.782</p>
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Revision as of 18:47, 17 October 2018

Modeling

Introduction

Since the effectuality of our genetic-modified parts are highly depended on the copper concentration of the outside environment, so it is significant to test the optimal copper concentration for the use of our product. With the consideration that using waste water collected from a factory will bring unnecessary factors other than the copper concentration and disable us to conclude the relation to the parts. We rather undergo complex mathematical process to calculate the predicted optimal concentration with the experimental data.

We have carried out several testing experiments to investigate the maximum capacity of both our medium, the e.coli, and e.coli with PcopA encoded in a comparably severe environment. We measured the fluorescence every two hours of E.coli in different concentration of copper solution (Cupric Chloride) , then the data sheets of E.coli growth against time against Copper(II) ion concentration have been achieved.

The following analysis is highly based on the sheets that we have attached, aiming to analyze the correlations between these two independent variables and how much these variables could cause the e.coli to be more active and effective at working.

Variable justification

Model development

1. The correlation of E.coli fluorescence against time against copper concentration

The data sheet we could obtain is shown below, which the side column represents the concentration of Cupric ion in a certain solution and the side row represents the time for e.coli bacteria placing in the solution. We have recorded 5 groups with one of them being the control group. And the result in this sheet will be analyzed in the following section.

Based on a common knowledge, both time and concentration will affect the bacterium’s growth, we had the first empirical equation, the two-variable linear function is then applied to test the simulation of these real-world data.

E = a × C + b × H + d (a, b, d are constants)

By the regression in the Matlab, we have obtained the function of E = 17.4 × C + 68.23 × H + 1181 where R2 = 0.782


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