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Team:TU-Munich/Modeling/Overview
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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> | <div class="box-left overview"><html><img src="https://static.igem.org/mediawiki/2013/9/91/TUM13_modeling-1.jpg" /></html> | ||
===Protein Predictions=== | ===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. | + | 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] |
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</div> | </div> | ||
<div class="box-right overview"><html><img src="https://static.igem.org/mediawiki/2013/2/28/TUM13_modeling-2.jpg" /></html> | <div class="box-right overview"><html><img src="https://static.igem.org/mediawiki/2013/2/28/TUM13_modeling-2.jpg" /></html> | ||
===Enzyme Kinetics=== | ===Enzyme Kinetics=== | ||
| - | For the effective implementation of our filter system it is essential to analyse the enzymatic activity of our effectors. Using experimental data we fitted the respective kinetic parameters and carried out rigorous uncertainty analysis to assess the reliability of the fitted parameters. | + | For the effective implementation of our filter system it is essential to analyse the enzymatic activity of our effectors. Using experimental data we fitted the respective kinetic parameters 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] |
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</div> | </div> | ||
<div class="box-left overview"><html><img src="https://static.igem.org/mediawiki/2013/b/b0/TUM13_modeling-3.jpg" /></html> | <div class="box-left overview"><html><img src="https://static.igem.org/mediawiki/2013/b/b0/TUM13_modeling-3.jpg" /></html> | ||
===Kill Switch=== | ===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. | + | 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.<br>[https://2013.igem.org/Team:TU-Munich/Modeling/Kill_Switch Read More] |
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</div> | </div> | ||
<div class="box-right overview"><html><img src="https://static.igem.org/mediawiki/2013/2/25/TUM13_modeling-4.jpg" /></html> | <div class="box-right overview"><html><img src="https://static.igem.org/mediawiki/2013/2/25/TUM13_modeling-4.jpg" /></html> | ||
===Filter Model=== | ===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. | + | 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.<br>[https://2013.igem.org/Team:TU-Munich/Modeling/Filter Read More] |
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</div> | </div> | ||
Revision as of 01:23, 5 October 2013
Modeling Overview
In our modeling efforts, we tried to cover a very wide range of different methods, ranging from simple ordinary differential equations, over partial differential equations to stochastic differential equations as well as bioinformatic methods. To gain the largest possible gain we stayed in close contact to the wetlab team and answered design question and fitted parameters that could then be used for implementation aspects.
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. Using experimental data we fitted the respective kinetic parameters 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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