Difference between revisions of "Team:UFSCar-Brasil/modelling.html"

 
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             Modelling
 
             Modelling
 
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           <h2>What we do</h2>
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           <h2>The mathematical explanation of our results, and how we can provide desired information</h2>
 
           <a href="#overview" class="ui huge inverted primary basic button">Overview<i class="right arrow icon"></i></a>
 
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           <h3 class="ui header" id="overview">Overview</h3>
 
           <h3 class="ui header" id="overview">Overview</h3>
            
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          <p>Our main purpose with modeling was to determine how deeply connected the collected data are and starting from this to make some previsions and take decisions. For this purpose, we have used several mathematical tools, since: analytic geometry, complex systems calculations to final tridimensional solutions. We hope that our previsions and mathematical models help the next teams and groups work better and harder, despite of course answer important questions of our current work.</p>
 
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           <h3 class="ui header" id="parts">Part I</h3>
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           <h3 class="ui header" id="parts">Plasmolysis</h3>
           <p>The purpose of this part of the modeling was to determine what would be the optimum absorbance and with it we would have funded the point relative to the longest time and the lowest percentage of PEG possible. For that were done some weeks of the experiment in the micro-biology laboratory. Then the data were processed and analyzed in order to find which one or ones would be that points. The analysis consisted initially in a model for which the system is most suited. After that, were found specific values which we analyze the simulated surface. Finally, we find the lines that tangents the surface where the point could be found. This study was of great significance when we realize that our project aims to find in stores and with this analysis is made possible to predict the validity of the product.
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           <p>This section proposes to determine what would be the longest time of bacterial maintenance with lowest possible percentage of PEG 6000. Plasmolysis experiments were performed in microbiology laboratory for some weeks. Collected data were processed and analyzed for best-fit model to those points. After that, using this model, it was built a simulated surface and specific values were found. Finally, we found tangent lines to the surface where our point of interest could be found. This study was of great significance when we realize that our project belongs to manufacturing tracking. Since it results in a product, and it should be found in stores, this analysis makes possible to predict the validity of the product and of its storage process.
 
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           <h3 class="ui header" id="result">Part II</h3>
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           <h3 class="ui header" id="result">Protein solubilization toolkit</h3>
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           <p>Desenvolvemos uma abordagem estatística para o estudo da eficiência das chaperonas no enovelamento da limoneno sintase. Com o intuito de criar uma método que melhor descreva a combinação de chaperonas com base nos dados de rendimento, criamos um dendograma que ilustra o agrupamento delas com base na distancia estatística dos seus rendimentos. Depois foi resolvido um sistema linear com todas as relações e encontrou-se constantes estatísticas de cada componente.</p>
           {{tag#math|H[z(<var>x</var>,<var>y</var>)] = \begin{vmatrix}
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\frac{\partial^2 <var>z</var>}{\partial x^2} & \frac{\partial^2 z}{\partial z,\partial y} \\
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\frac{\partial^2 z}{\partial z,\partial y} & \frac{\partial^2 z}{\partial y^2}
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           <h3 class="ui header" id="judging">Part III</h3>
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           <h3 class="ui header" id="judging">Kill Switch</h3>
 
           <p>One of our prime objective is to describe the activity of uspA promoter ( Universal Stress Protein A promoter) when exposed to osmotic chock compared with J23101 promoter. To quantify more precisely this behavior we adjust experimental points with general exponential functions and also related PEG concentration’s date with osmotic pressure. With the proper fitted curves, we modeled the concentration’s fall of Zn 2+ from external environment by import the metal to intracellular environment and gradually build up the smtA protein aiming estimate the approximate time for begin the death cell process, that initiate with the release of our killswitch’s promoter region due to the absence of Zn in cellular environmental to maintain the zur factor repressing ufscarA promoter. With the unblocked promoter, the transcription of death genes starts, metabolism and cell integrity is compromised leading to cell death.</p>
 
           <p>One of our prime objective is to describe the activity of uspA promoter ( Universal Stress Protein A promoter) when exposed to osmotic chock compared with J23101 promoter. To quantify more precisely this behavior we adjust experimental points with general exponential functions and also related PEG concentration’s date with osmotic pressure. With the proper fitted curves, we modeled the concentration’s fall of Zn 2+ from external environment by import the metal to intracellular environment and gradually build up the smtA protein aiming estimate the approximate time for begin the death cell process, that initiate with the release of our killswitch’s promoter region due to the absence of Zn in cellular environmental to maintain the zur factor repressing ufscarA promoter. With the unblocked promoter, the transcription of death genes starts, metabolism and cell integrity is compromised leading to cell death.</p>
  

Latest revision as of 14:14, 16 September 2015

Modelling

The mathematical explanation of our results, and how we can provide desired information

Overview

Overview

Our main purpose with modeling was to determine how deeply connected the collected data are and starting from this to make some previsions and take decisions. For this purpose, we have used several mathematical tools, since: analytic geometry, complex systems calculations to final tridimensional solutions. We hope that our previsions and mathematical models help the next teams and groups work better and harder, despite of course answer important questions of our current work.

Plasmolysis

This section proposes to determine what would be the longest time of bacterial maintenance with lowest possible percentage of PEG 6000. Plasmolysis experiments were performed in microbiology laboratory for some weeks. Collected data were processed and analyzed for best-fit model to those points. After that, using this model, it was built a simulated surface and specific values were found. Finally, we found tangent lines to the surface where our point of interest could be found. This study was of great significance when we realize that our project belongs to manufacturing tracking. Since it results in a product, and it should be found in stores, this analysis makes possible to predict the validity of the product and of its storage process.

Protein solubilization toolkit

Desenvolvemos uma abordagem estatística para o estudo da eficiência das chaperonas no enovelamento da limoneno sintase. Com o intuito de criar uma método que melhor descreva a combinação de chaperonas com base nos dados de rendimento, criamos um dendograma que ilustra o agrupamento delas com base na distancia estatística dos seus rendimentos. Depois foi resolvido um sistema linear com todas as relações e encontrou-se constantes estatísticas de cada componente.

Kill Switch

One of our prime objective is to describe the activity of uspA promoter ( Universal Stress Protein A promoter) when exposed to osmotic chock compared with J23101 promoter. To quantify more precisely this behavior we adjust experimental points with general exponential functions and also related PEG concentration’s date with osmotic pressure. With the proper fitted curves, we modeled the concentration’s fall of Zn 2+ from external environment by import the metal to intracellular environment and gradually build up the smtA protein aiming estimate the approximate time for begin the death cell process, that initiate with the release of our killswitch’s promoter region due to the absence of Zn in cellular environmental to maintain the zur factor repressing ufscarA promoter. With the unblocked promoter, the transcription of death genes starts, metabolism and cell integrity is compromised leading to cell death.

Our amazing sponsors!

Our amazing sponsors!