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

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<h1> Modeling</h1>
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<p>Mathematical models and computer simulations provide a great way to describe the function and operation of BioBrick Parts and Devices. Synthetic Biology is an engineering discipline, and part of engineering is simulation and modeling to determine the behavior of your design before you build it. Designing and simulating can be iterated many times in a computer before moving to the lab. This award is for teams who build a model of their system and use it to inform system design or simulate expected behavior in conjunction with experiments in the wetlab.</p>
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<h3> Gold Medal Criterion #3</h3>
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Convince the judges that your project's design and/or implementation is based on insight you have gained from modeling. This could be either a new model you develop or the implementation of a model from a previous team. You must thoroughly document your model's contribution to your project on your team's wiki, including assumptions, relevant data, model results, and a clear explanation of your model that anyone can understand.  
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The model should impact your project design in a meaningful way. Modeling may include, but is not limited to, deterministic, exploratory, molecular dynamic, and stochastic models. Teams may also explore the physical modeling of a single component within a system or utilize mathematical modeling for predicting function of a more complex device.
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Please see the <a href="https://2018.igem.org/Judging/Medals"> 2018
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Medals Page</a> for more information.
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<h3>Best Model Special Prize</h3>
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To compete for the <a href="https://2018.igem.org/Judging/Awards">Best Model prize</a>, please describe your work on this page  and also fill out the description on the <a href="https://2018.igem.org/Judging/Judging_Form">judging form</a>. Please note you can compete for both the gold medal criterion #3 and the best model prize with this page.
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You must also delete the message box on the top of this page to be eligible for the Best Model Prize.
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<h3> Inspiration </h3>
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Here are a few examples from previous teams:
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<li><a href="https://2016.igem.org/Team:Manchester/Model">2016 Manchester</a></li>
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<li><a href="https://2016.igem.org/Team:TU_Delft/Model">2016 TU Delft</li>
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<li><a href="https://2014.igem.org/Team:ETH_Zurich/modeling/overview">2014 ETH Zurich</a></li>
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<li><a href="https://2014.igem.org/Team:Waterloo/Math_Book">2014 Waterloo</a></li>
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        <h1>Modeling</h1>
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        <h2>Introduction</h2>
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        <p>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.</p>
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        <p>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.</p>
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        <p>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.</p>
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        <h2>Variable justification</h2>
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        <img src="https://static.igem.org/mediawiki/2018/9/91/T--ASTWS-China--var_justification.png">
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        <h2>Model development </h2>
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        <h3>1. The correlation of E.coli fluorescence against time against copper concentration </h3>
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        <p>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. </p>
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        <img src="https://static.igem.org/mediawiki/2018/a/a1/T--ASTWS-China--Model1.png">
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        <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 class="alignleft">Copyright &#169; 2018 Team:ASTWS-China All Rights Reserved.</p>
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                        <img class="alignright" id="QR" src="https://static.igem.org/mediawiki/2018/0/00/T--ASTWS-China--QR_Code.jpg">
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Revision as of 18:39, 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   w h i c h   a , b , d   a r e   c o n s t a n t                     ( 1 )

Copyright © 2018 Team:ASTWS-China All Rights Reserved.