Model Mathematics

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Component: environment

m = \frac{stimMag}{tR} q_LB1_stim = \{\begin{matrix} stimHolding + m ((time - stimSt) + tR) if time < stimSt \land time > stimSt - tR \\ stimMag + stimHolding if time \geq stimSt \land time < stimSt + stimDur \\ stimHolding + (- m) (time - stimSt - tR - stimDur) if time ≦ stimSt + tR + stimDur \land time \geq stimSt + stimDur \\ stimHolding otherwise \end{matrix}

v_Rsynthesis = 1 e -4 \frac{d}{d time} (q_RB1_inactive) = (- v_Rswitch_B1) + 0.0 v_Rsynthesis \frac{d}{d time} (q_L_RB1_inactive) = - v_LRswitch_B1 \frac{d}{d time} (q_LB1_ode) = - v_L_B1 \frac{d}{d time} (q_RB1) = v_Rswitch_B1 - v_C_B1 - v_L_B1 \frac{d}{d time} (q_Gs) = (- v_C_B1 - v_R_B1) + v_Reassoc_Gs \frac{d}{d time} (q_RB1_Gs) = v_C_B1 - v_Act1_Gs \frac{d}{d time} (q_L_RB1) = (v_LRswitch_B1 - v_R_B1) + v_L_B1 \frac{d}{d time} (q_L_RB1_Gs) = v_R_B1 - v_Act2_Gs \frac{d}{d time} (q_Gsa_GTP) = v_Act1_Gs + v_Act2_Gs - v_Hyd_Gs \frac{d}{d time} (q_Gsbetagamma) = v_Act1_Gs + v_Act2_Gs - v_Reassoc_Gs \frac{d}{d time} (q_Gsa_GDP) = v_Hyd_Gs - v_Reassoc_Gs \frac{d}{d time} (q_GTP) = - v_Act1_Gs - v_Act2_Gs \frac{d}{d time} (q_GDP) = v_Act1_Gs + v_Act2_Gs \frac{d}{d time} (q_Pi) = v_Hyd_Gs \frac{d}{d time} (q_RB1_tag) = v_Act1_Gs - v_InternR_B1 \frac{d}{d time} (q_L_RB1_tag) = v_Act2_Gs - v_InternLR_B1 \frac{d}{d time} (q_RB1_GRKArr) = v_InternR_B1 \frac{d}{d time} (q_L_RB1_GRKArr) = v_InternLR_B1 \frac{d}{d time} (q_GRKArr) = - v_InternR_B1 - v_InternLR_B1 q_LB1 = q_LB1_stim + q_LB1_ode

conserv_R_T = q_RB1_inactive + q_L_RB1_inactive + q_RB1 + q_RB1_Gs + q_L_RB1 + q_L_RB1_Gs + q_RB1_tag + q_L_RB1_tag + q_RB1_GRKArr + q_L_RB1_GRKArr conserv_L_T = q_L_RB1_inactive + q_LB1 + q_L_RB1 + q_L_RB1_Gs + q_L_RB1_tag + q_L_RB1_GRKArr conserv_G_T = q_Gs + q_RB1_Gs + q_L_RB1_Gs + q_Gsa_GTP + q_Gsa_GDP

Component: GPCR_B1AR_reduced_parameters

Component: GPCR_B1AR_reduced

mu_RB1_inactive = R T \ln (K_RB1_inactive q_RB1_inactive) mu_L_RB1_inactive = R T \ln (K_L_RB1_inactive q_L_RB1_inactive) mu_LB1 = R T \ln (K_LB1 q_LB1) mu_RB1 = R T \ln (K_RB1 q_RB1) mu_Gs = R T \ln (K_Gs q_Gs) mu_RB1_Gs = R T \ln (K_RB1_Gs q_RB1_Gs) mu_L_RB1 = R T \ln (K_L_RB1 q_L_RB1) mu_L_RB1_Gs = R T \ln (K_L_RB1_Gs q_L_RB1_Gs) mu_Gsa_GTP = R T \ln (K_Gsa_GTP q_Gsa_GTP) mu_Gsbetagamma = R T \ln (K_Gsbetagamma q_Gsbetagamma) mu_Gsa_GDP = R T \ln (K_Gsa_GDP q_Gsa_GDP) mu_GTP = R T \ln (K_GTP q_GTP) mu_GDP = R T \ln (K_GDP q_GDP) mu_Pi = R T \ln (K_Pi q_Pi) mu_RB1_tag = R T \ln (K_RB1_tag q_RB1_tag) mu_L_RB1_tag = R T \ln (K_L_RB1_tag q_L_RB1_tag) mu_RB1_GRKArr = R T \ln (K_RB1_GRKArr q_RB1_GRKArr) mu_L_RB1_GRKArr = R T \ln (K_L_RB1_GRKArr q_L_RB1_GRKArr) mu_GRKArr = R T \ln (K_GRKArr q_GRKArr) v_Rswitch_B1 = kappa_Rswitch_B1 (ⅇ^{\frac{mu_RB1_inactive}{R T}} - (ⅇ^{\frac{mu_RB1}{R T}})) v_LRswitch_B1 = kappa_LRswitch_B1 (ⅇ^{\frac{mu_L_RB1_inactive}{R T}} - (ⅇ^{\frac{mu_L_RB1}{R T}})) v_C_B1 = kappa_C_B1 (ⅇ^{\frac{mu_RB1 + mu_Gs}{R T}} - (ⅇ^{\frac{mu_RB1_Gs}{R T}})) v_R_B1 = kappa_R_B1 (ⅇ^{\frac{mu_L_RB1 + mu_Gs}{R T}} - (ⅇ^{\frac{mu_L_RB1_Gs}{R T}})) v_L_B1 = kappa_L_B1 (ⅇ^{\frac{mu_RB1 + mu_LB1}{R T}} - (ⅇ^{\frac{mu_L_RB1}{R T}})) v_Act1_Gs = kappa_Act1_Gs (ⅇ^{\frac{mu_RB1_Gs + mu_GTP}{R T}} - (ⅇ^{\frac{mu_Gsa_GTP + mu_Gsbetagamma + mu_RB1_tag + mu_GDP}{R T}})) v_Act2_Gs = kappa_Act2_Gs (ⅇ^{\frac{mu_L_RB1_Gs + mu_GTP}{R T}} - (ⅇ^{\frac{mu_Gsa_GTP + mu_Gsbetagamma + mu_L_RB1_tag + mu_GDP}{R T}})) v_Hyd_Gs = kappa_Hyd_Gs (ⅇ^{\frac{mu_Gsa_GTP}{R T}} - (ⅇ^{\frac{mu_Gsa_GDP + mu_Pi}{R T}})) v_Reassoc_Gs = kappa_Reassoc_Gs (ⅇ^{\frac{mu_Gsa_GDP + mu_Gsbetagamma}{R T}} - (ⅇ^{\frac{mu_Gs}{R T}})) v_InternR_B1 = kappa_InternR_B1 (ⅇ^{\frac{mu_RB1_tag + mu_GRKArr}{R T}} - (ⅇ^{\frac{mu_RB1_GRKArr}{R T}})) v_InternLR_B1 = kappa_InternLR_B1 (ⅇ^{\frac{mu_L_RB1_tag + mu_GRKArr}{R T}} - (ⅇ^{\frac{mu_L_RB1_GRKArr}{R T}}))

Model Mathematics

Component: environment

Component: GPCR_B1AR_reduced_parameters

Component: GPCR_B1AR_reduced

Component: units

Component: constants