Difference between revisions of "Team:UFSCar-Brasil/Modeling"

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           <h3 class="ui header" id="overview">Overview</h3>
 
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         <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> Modeling was made using differential calculus with analytical geometry approaches. Tridimensional solutions were a resource used to explain the multivariable systems obtained in our anlyzes. This joint approach was chosen to comprise all expected data and provides usefull evidences of non-validated data. First of all, Bugshoo is a product and in this manufacturing tracking, we must to answer several questions not testable in lab, in our time at least, like product expiration date. Besides this, some project parts have a complex functioning as kill switch and a mathematical model could help to determine the effective time of product working. The effectiveness of the product is another important question, for this, some economic solutions, e.g. reduction of PEG 6000 in final formula, optimal zinc chloride concentrations and another parameters could be adjusted with modeling aid. Main used softwares were OriginLab and MatLab. In this sense, we still want to determine the current project as predictive since some parts of it were not produced and the modeling still is passive to work.</p>
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           <h3 class="ui header" id="parts">Plasmolysis</h3>
 
           <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.
+
           <p>Main purpose of plasmolysis modeling was to determine a relative point, where we have the longest time of bacterial viability and lowest possible percentage of PEG 6000. In order to do that, it was carried out a plasmolysis experiment in our microbiology laboratory for some weeks, along we collected the data. Collected data were processed and analyzed to find a best-fit model. Using it, specific values were simulated to generate a mathematical surface. Finally, tangent lines to surface revealed the optimal point. Manufacturing tracking is known by its practical nature, and this study was significant to determine the conditions of product storage, besides revealing a technique very useful to other teams in future. Furthermore, this approach provided a prediction of optimal features for maximal product expiration date.
 
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Revision as of 15:01, 16 September 2015

Modeling

Mathematics explaining and predicting events

Overview

Overview

Modeling was made using differential calculus with analytical geometry approaches. Tridimensional solutions were a resource used to explain the multivariable systems obtained in our anlyzes. This joint approach was chosen to comprise all expected data and provides usefull evidences of non-validated data. First of all, Bugshoo is a product and in this manufacturing tracking, we must to answer several questions not testable in lab, in our time at least, like product expiration date. Besides this, some project parts have a complex functioning as kill switch and a mathematical model could help to determine the effective time of product working. The effectiveness of the product is another important question, for this, some economic solutions, e.g. reduction of PEG 6000 in final formula, optimal zinc chloride concentrations and another parameters could be adjusted with modeling aid. Main used softwares were OriginLab and MatLab. In this sense, we still want to determine the current project as predictive since some parts of it were not produced and the modeling still is passive to work.

Plasmolysis

Main purpose of plasmolysis modeling was to determine a relative point, where we have the longest time of bacterial viability and lowest possible percentage of PEG 6000. In order to do that, it was carried out a plasmolysis experiment in our microbiology laboratory for some weeks, along we collected the data. Collected data were processed and analyzed to find a best-fit model. Using it, specific values were simulated to generate a mathematical surface. Finally, tangent lines to surface revealed the optimal point. Manufacturing tracking is known by its practical nature, and this study was significant to determine the conditions of product storage, besides revealing a technique very useful to other teams in future. Furthermore, this approach provided a prediction of optimal features for maximal product expiration date.

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.

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