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Team:Tsinghua-A/Modeling/GILLESPIE/part2
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<p>Here,<img src="https://static.igem.org/mediawiki/2012/2/2b/THU-AMGP25.png"/>are the probabilities of the reaction in an | <p>Here,<img src="https://static.igem.org/mediawiki/2012/2/2b/THU-AMGP25.png"/>are the probabilities of the reaction in an | ||
Infinitesimal time. According to the property of the Markov chain , we can get:</p> | Infinitesimal time. According to the property of the Markov chain , we can get:</p> | ||
| - | + | <img src="https://static.igem.org/mediawiki/2012/d/db/THU-AMGP26.png"/> | |
| + | <p>In the model,<img src="https://static.igem.org/mediawiki/2012/1/16/THU-AMGP27.png"/>is proportional to the concentration of Cre-Loxp and<img src="https://static.igem.org/mediawiki/2012/d/d7/THU-AMGP28.png"/>are much larger than<img src="https://static.igem.org/mediawiki/2012/1/11/THU-AMGP29.png"/></p> | ||
</div> | </div> | ||
Revision as of 04:53, 26 September 2012
Tsinghua-A::Modeling
Our model
In our model , we use Gillespie algorithm to simulate the process of inversion. Here we use Markov chain to describe the process of inversion. We assume that the state ‘A’ , ‘B’ , ‘C’ , ‘D’ , is the original state , the state after inversion , the Intermediate state when A forms holiday junction, the Intermediate state when B forms holiday junction respectively.
(VAN DUYNE G D, 2001)
(VAN DUYNE G D, 2001)
The following are the reactions which are related to the process of inversion.
Then we get the following Markov chain.
Here,
are the probabilities of the reaction in an
Infinitesimal time. According to the property of the Markov chain , we can get:
In the model,
is proportional to the concentration of Cre-Loxp and
are much larger than
