Team:Amsterdam/data/background activity

From 2012.igem.org

(Difference between revisions)
(Leakiness and background noise)
(Leakiness and background noise)
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=Leakiness and background noise=
=Leakiness and background noise=
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This model has as its main goal to identify how much the uninduced operon expression rate and the catalysis rate of the FP affect the methylation status of the plasmids.
 
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Each plasmid is assumed to have one bit and one operon that includes the fusion protein.
 
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Running the stochastic version of this model, we noticed that keeping the amount of equations to a minimum is paramount to success, as the computation time seems to increase exponentially with the amount of reactions in the system.
 
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Focussing on the leakiness rate instead of the repressor-operon interactions that would require a lot of equations, we will therefore make one bold assumption:
 
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all operons present in a single cell are permanently bound to a transcriptional repressor.
 
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This frees us from having to code the signal entering the cell and binding the repressing TF, granting focus to the leaky expression rate and the catalysis rate of the fusion protein. 
 
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For these models to have any forecastable value therefore, the amount of repressor molecules present in the system has to be much greater than the amount required to cover all operons.
 
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In order to not exclude the possible qualitative difference in model behaviour when all molecular reactions are computed individually, the system has also been modelled stochastically. To make the two systems perfectly comparable, the used rates are qualitatively identical to the ones used in the ODE system.
 
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Furthermore, the same parameter values have been used.
 
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<table align="right">
<table align="right">
<tr><th>Parameter</th><th>Value</th></tr>
<tr><th>Parameter</th><th>Value</th></tr>
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     </tr>
     </tr>
</table>
</table>
 +
This model has as its main goal to identify how much the uninduced operon expression rate and the catalysis rate of the FP affect the methylation status of the plasmids.
 +
Each plasmid is assumed to have one bit and one operon that includes the fusion protein.
 +
Running the stochastic version of this model, we noticed that keeping the amount of equations to a minimum is paramount to success, as the computation time seems to increase exponentially with the amount of reactions in the system.
 +
Focussing on the leakiness rate instead of the repressor-operon interactions that would require a lot of equations, we will therefore make one bold assumption:
 +
all operons present in a single cell are permanently bound to a transcriptional repressor.
 +
This frees us from having to code the signal entering the cell and binding the repressing TF, granting focus to the leaky expression rate and the catalysis rate of the fusion protein. 
 +
For these models to have any forecastable value therefore, the amount of repressor molecules present in the system has to be much greater than the amount required to cover all operons.
 +
 +
In order to not exclude the possible qualitative difference in model behaviour when all molecular reactions are computed individually, the system has also been modelled stochastically. To make the two systems perfectly comparable, the used rates are qualitatively identical to the ones used in the ODE system.
 +
Furthermore, the same parameter values have been used.
 +
 +
==ODE Model definition==
==ODE Model definition==

Revision as of 01:44, 27 September 2012