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| - | <h2 id="titleText" style="color:rgb(137,202,154);">Tsinghua-A::Modeling</h2> | + | <h2 id="titleText" style="color:rgb(137,202,154);">Tsinghua-A::Modeling::<span style="color: rgb(12,117,34);">GILLESPIE Algorithm</span></h2> |
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| | <p>the reverse process of the gene between the two Loxp sites could not be well described by the DDE or ODE equations since after the reverse process, the gene will have chance to flip again. This process is a discrete, stochastic process instead of a continuous, deterministic process. To make the model more convincing, we use Gillespie algorithm, which is a kind of stochastic simulation algorithm to generate a statistically correct trajectory (possible solution) of a stochastic equation.<a class="textLink" href="https://2012.igem.org/Team:Tsinghua-A/Modeling/GILLESPIE/part1">readmore</a> | | <p>the reverse process of the gene between the two Loxp sites could not be well described by the DDE or ODE equations since after the reverse process, the gene will have chance to flip again. This process is a discrete, stochastic process instead of a continuous, deterministic process. To make the model more convincing, we use Gillespie algorithm, which is a kind of stochastic simulation algorithm to generate a statistically correct trajectory (possible solution) of a stochastic equation.<a class="textLink" href="https://2012.igem.org/Team:Tsinghua-A/Modeling/GILLESPIE/part1">readmore</a> |
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| - | <h2 class="textTitle" style="font-size:38px;">Our model using Gillespie algorithm</h2> | + | <h2 class="textTitle" style="font-size:38px;">Our model</h2> |
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| | <p>In our model , we use Gillespie algorithm to simulate the process of inversion. Here we use | | <p>In our model , we use Gillespie algorithm to simulate the process of inversion. Here we use |
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| | Intermediate state when A forms holiday junction, the Intermediate state when B forms holiday | | Intermediate state when A forms holiday junction, the Intermediate state when B forms holiday |
| | junction respectively. | | junction respectively. |
| - | <a class="textLink" href="https://2012.igem.org/Team:Tsinghua-A/Modeling/part2">readmore</a></p> | + | <a class="textLink" href="https://2012.igem.org/Team:Tsinghua-A/Modeling/GILLESPIE/part2">readmore</a></p> |
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Tsinghua-A::Modeling::GILLESPIE Algorithm
Gillespie algorithm
the reverse process of the gene between the two Loxp sites could not be well described by the DDE or ODE equations since after the reverse process, the gene will have chance to flip again. This process is a discrete, stochastic process instead of a continuous, deterministic process. To make the model more convincing, we use Gillespie algorithm, which is a kind of stochastic simulation algorithm to generate a statistically correct trajectory (possible solution) of a stochastic equation.readmore
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.
readmore
A better model
1000 genes which are in state ‘A’ are seen as a whole in the above model. To make the simulation more convincing, we then simulate the trajectory of every single molecule. After that we synthesize all trajectories to get the final result.readmore
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