Team:Michigan/Project/Modeling/Model3

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Using Mathematica's xCellerator program, we ran a Gillespie Integration of our system, and its corresponding ODE simulation with the same parameters (appropriately scaled to fit in the ODE context of concentration vs. stochastic context of number of proteins).
Using Mathematica's xCellerator program, we ran a Gillespie Integration of our system, and its corresponding ODE simulation with the same parameters (appropriately scaled to fit in the ODE context of concentration vs. stochastic context of number of proteins).
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[[Image: Stochastic.png]] [[Image:odesto.png]]

Revision as of 02:59, 30 October 2008


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Sequestillator Model 3: Stochastic Model

Using Mathematica's xCellerator program, we ran a Gillespie Integration of our system, and its corresponding ODE simulation with the same parameters (appropriately scaled to fit in the ODE context of concentration vs. stochastic context of number of proteins). Stochastic.png Odesto.png


I ran multiple stochastic results, and I got similar results to the one above. We see that there isn't really a constant period or amplitude; yet, it seems that there is some oscillatory potential, and that this is not pure noise. Note that ODE simulation goes quickly to a steady state. This model brings up two interesting points:

  • The Ninfa index of our system maybe larger than predicted, since we did not account for our stochastic effects.
  • We may see oscillations in our experiments, even if our simulations point to no chance of oscillations.

We could not run Ninfa index searches using the Indexilator on these stochastic simulations, due to the slowness of the xCellerator program and because our Indexilator can only evaluate ODE results, and not these noisy ones.



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