Team:Tsinghua-A/Modeling/Feedforward
From 2012.igem.org
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<h2 style="margin-top:135px; ">System design</h2> | <h2 style="margin-top:135px; ">System design</h2> | ||
- | <img src="https://static.igem.org/mediawiki/2012/e/e7/THU-AMF1.png"/> | + | <img src="https://static.igem.org/mediawiki/2012/e/e7/THU-AMF1.png" width="600px"/> |
- | <p>The above figure means that we want to produce | + | <p>The above figure means that we want to produce spermidine after a certain time we add arabinose which can reduce the activity of Cre. Then the number of times of flip will decrease and we can expect to get more genes in state ‘B’ we want. |
- | Below is the reaction we add to achieve the idea. Here <img src="https://static.igem.org/mediawiki/2012/b/b4/THU-AMF2.png"/> denotes time delay. s denotes | + | Below is the reaction we add to achieve the idea. Here <img src="https://static.igem.org/mediawiki/2012/b/b4/THU-AMF2.png"/> denotes time delay. s denotes spermidine.<img src="https://static.igem.org/mediawiki/2012/b/b5/THU-AMF3.png"/>denote the production rate of s, the degradation rate of s, the degradation rate of Cre with the affection of s respectively.</br> |
<img src="https://static.igem.org/mediawiki/2012/8/85/THU-AMF4.png"/> | <img src="https://static.igem.org/mediawiki/2012/8/85/THU-AMF4.png"/> | ||
</p> | </p> | ||
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<p> 1 trajectory: </p> | <p> 1 trajectory: </p> | ||
<img src="https://static.igem.org/mediawiki/2012/1/1e/THU-AMF7.png"/> | <img src="https://static.igem.org/mediawiki/2012/1/1e/THU-AMF7.png"/> | ||
- | <p> 10 | + | <p> 10 trajectories: </p> |
<img src="https://static.igem.org/mediawiki/2012/7/70/THU-AMF8.png"/> | <img src="https://static.igem.org/mediawiki/2012/7/70/THU-AMF8.png"/> | ||
- | <p> 100 | + | <p> 100 trajectories: </p> |
<img src="https://static.igem.org/mediawiki/2012/0/07/THU-AMF9.png"/> | <img src="https://static.igem.org/mediawiki/2012/0/07/THU-AMF9.png"/> | ||
- | <p> 1000 | + | <p> 1000 trajectories: </p> |
<img src="https://static.igem.org/mediawiki/2012/6/6e/THU-AMF10.png"/> | <img src="https://static.igem.org/mediawiki/2012/6/6e/THU-AMF10.png"/> | ||
<p>Compare the result of the model with feed forward with the previous one without feed forward, we can easily find that:</br> | <p>Compare the result of the model with feed forward with the previous one without feed forward, we can easily find that:</br> |
Latest revision as of 17:36, 26 September 2012
Tsinghua-A::Modeling::Feedforward
System design
The above figure means that we want to produce spermidine after a certain time we add arabinose which can reduce the activity of Cre. Then the number of times of flip will decrease and we can expect to get more genes in state ‘B’ we want. Below is the reaction we add to achieve the idea. Here denotes time delay. s denotes spermidine.denote the production rate of s, the degradation rate of s, the degradation rate of Cre with the affection of s respectively.
Results
The concentration of Cre :
The concentration of Cre-Loxp :
The number of the genes in different states:
1 trajectory:
10 trajectories:
100 trajectories:
1000 trajectories:
Compare the result of the model with feed forward with the previous one without feed forward, we can easily find that: 1. The peak of the Cre distribution is narrower in the model with a feed forward part and the number of times of flip decreases a lot. 2. In the stable state that the number of genes in every state does not change any more, more genes have flipped from state ‘A’ to state ‘B’ in the model with a feed forward part. And this result is better than the previous one since we want the system to finally change from the ‘AND’ gate to the ‘OR’ gate which means it is better to have more genes in state ‘B’.
Stability analysis:
We then compare the stability of the system with feed forward with the previous one without feed forward by observing their phase trajectories and we can get the following result. System without feed forward:
System with feed forward:
Both phase trajectories of the two systems go straight to a point which illustrate that both systems reach to the stable state rapidly. But if we observe carefully, we can see some fluctuations in the Figure 4.8 and almost no fluctuation in Figure 4.9 from which we can get the conclusion that the system with feed forward is more stable than the one without feed forward.