Team:UPO-Sevilla/Project/Basic Flip Flop/Modeling/Other Models
From 2011.igem.org
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- | + | <p>The ‘trigger’ is just the moments where we simulate the effect of adding IPTG or increasing temperature. Even, the parameters are the same as the last Simbiology simulation.</p> | |
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+ | <p>If we run this program, it offers the following result:</p> | ||
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+ | <div class="center"> | ||
+ | <img src="https://static.igem.org/mediawiki/2011/c/c3/Sim33.jpg" alt="Translation 1 Rate" /> | ||
+ | </div> | ||
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+ | <h2>Basic Toggle Switch General Equation Model with Simulink</h2> | ||
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+ | <p>Here we present another implementation on Simulink, using Matlab again.</p> | ||
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+ | <p>In the model we have included the overall process of the transcription and translation as a first-order kinetic model. The only exception to that vision is that the repression is treated as a modifier of the Michaelis constant of the transcription.</p> | ||
+ | |||
+ | <p>The diagram of the process is the following:</p> | ||
+ | |||
+ | |||
+ | <div class="center"> | ||
+ | <img src="https://static.igem.org/mediawiki/2011/e/eb/Simulink_scheme.jpg" alt="Translation 1 Rate" /> | ||
+ | </div> | ||
+ | |||
+ | <p>These results show no relevant information with respect to the models already presented. But the way to implement the system is closer to the vision of systems theory. Under this environment, we show all processes as first order systems.</p> | ||
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</div> | </div> |
Revision as of 17:36, 20 September 2011
Other Models
Now, we show a different vision of the model presented. All of them are implemented in Matlab’s scripts or using the Simulink tool.
Basic Toggle switch general Equation Model
Here we have integrated the equations using the Euler approximation method. In spite of the overall behavior may change, the results obtained show a similar approximation to the previous graphics.
We are using this new method to show a different integration method than the used before. Furthermore, here we use a discrete approximation facing the previous. It is easier to show how the repression acts as modifier of the Michaelis constant of transcription process.
The algorithm used evaluates each species and its change in every step of the algorithm. So the algorithm is:
for t=1:(tsim-1)
Km_1=Km1*(1+Rep2(t)/Kiv)^beta;
Km_2=Km2*(1+r1(t)/Kiu)^gamma;
mRNA1(t+1)=abs(mRNA1(t)+tau*(Lambda1*RNAp/(Km_1+RNAp)-delta1*mRNA1(t)));
mRNA2(t+1)=abs(mRNA2(t)+tau*(Lambda2*RNAp/(Km_2+RNAp)-delta2*mRNA2(t)));
trigger
k1=Kc1*mRNA1(t+1,1);
k2=Kc2*mRNA2(t+1,1);
Rep1(t+1)=abs(Rep1(t)+tau*(k1*Rib/(Kmu+Rib)-d1*Rep1(t)));
Rep2(t+1)=abs(Rep2(t)+tau*(k2*Rib/(Kmv+Rib)-(d2+ktemp)*Rep2(t)));
r1(t+1)=(Rep1(t+1)/K)/((1+IPTG/Ki)^eta);
end
The ‘trigger’ is just the moments where we simulate the effect of adding IPTG or increasing temperature. Even, the parameters are the same as the last Simbiology simulation.
If we run this program, it offers the following result:
Basic Toggle Switch General Equation Model with Simulink
Here we present another implementation on Simulink, using Matlab again.
In the model we have included the overall process of the transcription and translation as a first-order kinetic model. The only exception to that vision is that the repression is treated as a modifier of the Michaelis constant of the transcription.
The diagram of the process is the following:
These results show no relevant information with respect to the models already presented. But the way to implement the system is closer to the vision of systems theory. Under this environment, we show all processes as first order systems.