Team:PKU Beijing/Modeling/Stochastic

From 2009.igem.org

Revision as of 07:06, 20 October 2009 by Lug7 (Talk | contribs)

Modeling

Modeling Home
ODE
Parameters
Result
Stochastic Model
Improvement

 
Modeling > Stochastic Model

We have successfully conduct ODE model for both T3 design and P2 design. However, there's a inborn defect. The ODE models regard memory as a switch, only two state - 0 and 1. Actually, the memory is continous. Besides that, since the number of molecules in cell is not large enough, which means the circuit itself has a stochastic property. For these reasons, we conduct a stochastic model. Since ODE model for P2 is not as good as the one for T3, we will only conduct stochastic model for the T3 design.

Construction

New model needs new equations. In stochastic model, the equations should represent more elementary reactions. So we split the 13 equations in our deterministic model into 29 more elementary ones. Here we'll demonstrate these equations, without much explaination. If you're confused by some equations, please visit ODE page, on which there're detailed explainations for each equation we used.

EquationsRemark
d[tRNA]/dt=Synthesis of tRNA
Degradation of tRNA
Transformation from tRNA to Aa-tRNA
Degradation of Aa-tRNA (Aa-tRNA->tRNA)
Dilution of Aa-tRNA
Transcription of T7RNAP
Degradation of T7RNAP
AND Gate 1
Degradation of T7RNAP protein
Transcription of trigger CI
Transcription of Bistable CI
Degradation of trigger CI mRNA
Degradation of bistable CI mRNA
Translation of trigger CI mRNA
Translation of bistable CI mRNA
Degradation of CI protein
Transcription of CI434
Degradation of CI434 mRNA
Translation of CI434 mRNA
Degradation of CI434 mRNA
Transcription of T3
Degradation of T3 mRNA
AND Gate 2
Degradation of T3
Transcription of GFP - OR Gate
Transcription of GFP - AND Gate - OR Gate
Degradation of GFP mRNA
Translation of GFP mRNA
Degradation of GFP

Parameters

Generally, we just use the parameters from our ODE model, just to keep consistent. However, we did change a few, mainly translation rate of CI and CI434, aiming at simulating learning process and forgetting process. Here's the parameters we used. You can also visit parameters page for more detailed information.

Result



^Top