Team:TU-Munich/Modeling/Overview

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Revision as of 18:20, 4 October 2013

Modeling Overview

Protein Predictions

For the immobilisation of effectors on the cell membrane, we needed to design a transmembrane domain. Using several bioinformatic methods we identified the transmembrane region of the SERK receptor which we later used as starting point for our constructs. (Read More)

Enzyme Kinetics

For the effective implementation of our filter system it is essential to analyse the enzymatic activity of our effectors. To do this in a sophisticated fashion, we carried out a series of in vitro assays with different concentrations. Using this experimental data we fitted the kinetic parameters for the enzymatically catalized conversion reaction and carried out rigorous uncertainty analysis to assess the reliability of the fitted parameters. (Read More)

Kill Switch

During the planning stage of our project, we had several different ideas on how to efficiently implement a kill-switch in our moss. In this section of the wiki we documented our mathematical train of thought that eventually led us to our final design. (Read More)

Filter Model

The filter model is aimed to simulate different remediation scenarios and should be used to calculate the perfectly fitting conditions of our Physco filter, referring to the needs of the environment. (Read More)

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 <div class="box-left overview"><html><img src="https://static.igem.org/mediawiki/2013/9/91/TUM13_modeling-1.jpg" /></html>
 ===Protein Predictions===
-Lorem ipsum dolor sit amet, consetetur sadipscing elitr, molker schmollath sed diam nonumy eirmod tempor invidunt ut labore et dolore magna aliquyam erat, sed diam voluptua.
+For the immobilisation of effectors on the cell membrane, we needed to design a transmembrane domain. Using several bioinformatic methods we identified the transmembrane region of the SERK receptor which we later used as starting point for our constructs.
 ([https://2013.igem.org/Team:TU-Munich/Modeling/Protein_Predictions Read More])
 </div>
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 <div class="box-right overview"><html><img src="https://static.igem.org/mediawiki/2013/2/28/TUM13_modeling-2.jpg" /></html>
 ===Enzyme Kinetics===
-Proper analysis of data is important to really understand them. For this reason we formed groups in which our wet and dry lab people came together to understand our experiments from an experimental as well as mathematical point of view.
+For the effective implementation of our filter system it is essential to analyse the enzymatic activity of our effectors. To do this in a sophisticated fashion, we carried out a series of ''in vitro'' assays with different concentrations. Using this experimental data we fitted the kinetic parameters for the enzymatically catalized conversion reaction and carried out rigorous uncertainty analysis to assess the reliability of the fitted parameters.
 ([https://2013.igem.org/Team:TU-Munich/Modeling/Enzyme Read More])
 </div>
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 <div class="box-left overview"><html><img src="https://static.igem.org/mediawiki/2013/b/b0/TUM13_modeling-3.jpg" /></html>
 ===Kill Switch===
-Especially during planing seasons, we had several different ideas in which way our moss could detect on its own that it has escaped from its appropriate environment, how the resulting signal is triggered and how it should decrease its viablility.
+During the planning stage of our project, we had several different ideas on how to efficiently implement a kill-switch in our moss. In this section of the wiki we documented our mathematical train of thought that eventually led us to our final design.
 ([https://2013.igem.org/Team:TU-Munich/Modeling/Kill_Switch Read More])
 </div>