Tokyo/Works/Simulation

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Works top  0.Hybrid promoter  1.Formulation  2.Assay1  3.Simulation  4.Assay2  5.Future works

シミュレーションはpopulationモデルに拡張し,確率微分方程式を用いた

Ex3.1 the differential equations of population model



Ex3.2 the stochastic differential equations of the population model



What we have found so far

Wet experiments have determined Hill coefficients, coefficients of repression and activation of AHL and LacI(n2,n3,k2,k3) as follows.


n2 = 2.08 (-)
K2 = 4.05 (μM)
n3 = 2.47 (-)
K3 = 0.295 (μM)

Determining the range of parameter which satisfy coexistent stability

The example of coexistent stable state

Fig.1.A  t=0.0(min)
Arrow2.JPG
Fig.1.B  t=3.0(min)
Arrow2.JPG
Fig.1.C   t=30(min) only A

⇒ movie here!!

Fig.2.A  t=0.0(min)
Arrow2.JPG
Fig.2.B  t=3.0(min)
Arrow2.JPG
Fig.2.C   t=30(min) A and B are coexistence!!

⇒ movie here!!

Fig.3.A  t=0.0(min)
Arrow2.JPG
Fig.3.B  t=3.0(min)
Arrow2.JPG
Fig.3.C   t=30(min) only B

⇒ movie here!!


For the three patterns, the phase portraits at the moment when the number of the intersection of nullclines become two are shown in Fig.4.A-C respectively.

Fig.4.A
Fig.4.B
Fig.4.C


Fig.4.A shows that when the two equilibrium points appeared, cells were existing closer to A-side than the unstable equilibrium point. Oppositely,in Fig.4.C,when the two equilibrium points appeared, cells were existing closer to A-side than the unstable equiliblium point. Since when the number of the intersection of nullclines becomes two, stable point appears on B-side, at the moment of Fig.4, cells on the A-side cannot transit to B-side across unstble equilibrium point. As a result, all cells transit to A-side.


⇒ movie about Fig.4.A here!!

⇒ movie about Fig.4.B here!!

⇒ movie about Fig.4.C here!!

The range of parameter λ

To determine the range of parameter λ, several simulations were conducted with different values of λ. As a result, the relationship between λ value and the probability of coexistence is determined as shown in Fig.5.

Fig.5

By using parameter λ in this range, we can construct our model.