def simulate(self, x, y0, _perturbation={}):
if _perturbation:
self.perturbation = _perturbation
for gene_name in self.obs_names:
x = self._set_gene_param(gene_name, x)
for i, condition in enumerate(self.conditions):
if condition == "WT":
y0[V.S2] = x[C.S2tot]
y0[V.S3] = x[C.S3tot]
y0[V.S4] = x[C.S4tot]
elif condition == "Smad2OE":
y0[V.S2] = 2 * x[C.S2tot]
y0[V.S3] = x[C.S3tot]
y0[V.S4] = x[C.S4tot]
elif condition == "Smad3OE":
y0[V.S2] = x[C.S2tot]
y0[V.S3] = 16 * x[C.S3tot]
y0[V.S4] = x[C.S4tot]
elif condition == "Smad4OE":
y0[V.S2] = x[C.S2tot]
y0[V.S3] = x[C.S3tot]
y0[V.S4] = 3 * x[C.S3tot]
sol = solve_ode(self.diffeq, y0, self.t, tuple(x))
if sol is None:
return False
else:
self.simulations[self.obs_names.index(gene_name), :,
i] = np.log2(sol.y[V.gene, :])
def simulate(self, x, y0, _perturbation=None):
if _perturbation is not None:
self.perturbation = _perturbation
for i, condition in enumerate(self.conditions):
if condition == "control":
pass
"""
elif condition == 'cooperative':
x[C.n] = 2
x[C.KI] = 18
x[C.K1] = 50
x[C.K2] = 40
x[C.K3] = 100
x[C.K4] = 100
x[C.K5] = 100
x[C.K6] = 100
x[C.K7] = 100
x[C.K8] = 100
x[C.K9] = 100
x[C.K10] = 100
x[C.V9] = 1.25
x[C.V10] = 1.25
"""
sol = solve_ode(self.diffeq, y0, self.t, tuple(x))
if sol is None:
return False
else:
self.simulations[self.obs_names.index("biphosphorylated_MAPK"), :, i] = sol.y[
V.MAPK_PP, :
]
self.simulations[self.obs_names.index("unphosphorylated_MAPK"), :, i] = sol.y[
V.MAPK, :
]
def simulate(self, x, y0, _perturbation={}):
if _perturbation:
self.perturbation = _perturbation
for i, condition in enumerate(self.conditions):
if condition == "TNFa":
pass
elif condition == "TNFa_DCF":
x[C.uptake] = 1.0000
x[C.TNF] = 1.0000
x[C.trigger_iIkk] = 0.0195
x[C.deact_TNFR] = 0.0010
x[C.deact_ppIkk] = 0.1660
x[C.deact_pnNfk] = 1000.0000
x[C.act_Ikk_by_TNF] = 0.0347
x[C.act_pIkk] = 0.1603
x[C.act_Ikb_by_Ikk] = 0.1562
x[C.act_Nfk_by_Ikk] = 0.6438
x[C.act_Nfk_by_Ikk_complex] = 0.2816
x[C.act_Ikb_complex] = 1.3897
x[C.form_complex] = 2.8390
x[C.form_complex_nuc] = 1000.0000
x[C.ext_nNfkIkb] = 1000.0000
x[C.Vnuc] = 1.0000
x[C.split_NfkpIkb] = 0.0811
x[C.split_NfkIkb] = 1.0000
x[C.int_Nfk] = 0.0100
x[C.int_Ikb] = 0.1226
x[C.eta_int_pNfk] = 17.9585
x[C.degrad_Ikb] = 0.6308
x[C.degrad_mIkb] = 0.0053
x[C.degrad_RnaA20] = 0.0089
x[C.degrad_A20] = 0.0116
x[C.prod_Ikb] = 1.0000
x[C.prod_mIkb_by_nNfk] = 0.0020
x[C.build_RnaA20] = 1.0000
x[C.build_A20] = 0.0006
x[C.shuttle_RnaA20] = 0.0119
sol = solve_ode(self.diffeq, y0, self.t, tuple(x))
if sol is None:
return False
else:
self.simulations[self.obs_names.index("nuclear_IkBa"), :,
i] = x[C.Vnuc] * (sol.y[V.nNfkIkb, :] +
sol.y[V.nIkb, :])
self.simulations[self.obs_names.index("nuclear_NFkB"), :,
i] = x[C.Vnuc] * (sol.y[V.pnNfk, :] +
sol.y[V.nNfk, :] +
sol.y[V.nNfkIkb, :])
def simulate(self, x, y0, _perturbation={}):
if _perturbation:
self.perturbation = _perturbation
for i, condition in enumerate(self.conditions):
if condition == "DD":
pass
sol = solve_ode(self.diffeq, y0, self.t, tuple(x))
if sol is None:
return False
else:
self.simulations[self.obs_names.index("Per_mRNA"), :, i] = sol.y[V.MP, :]
self.simulations[self.obs_names.index("Cry_mRNA"), :, i] = sol.y[V.MC, :]
self.simulations[self.obs_names.index("Bmal1_mRNA"), :, i] = sol.y[V.MB, :]
def simulate(self, x, y0, _perturbation={}):
if _perturbation:
self.perturbation = _perturbation
y0[V.Ins] = 0.01 # 0.01 nM of insulin during starvation
sol = solve_ode(self.diffeq, y0, range(2400 + 1), tuple(x))
if sol is None:
return False
else:
y0 = sol.y[:, -1].tolist()
for i, condition in enumerate(self.conditions):
if condition == "Insulin 0.01":
y0[V.Ins] = 0.01
elif condition == "Insulin 0.03":
y0[V.Ins] = 0.03
elif condition == "Insulin 0.1":
y0[V.Ins] = 0.1
elif condition == "Insulin 0.3":
y0[V.Ins] = 0.3
elif condition == "Insulin 1.0":
y0[V.Ins] = 1.0
sol = solve_ode(self.diffeq, y0, self.t, tuple(x))
if sol is None:
return False
else:
self.simulations[self.obs_names.index("pAKT"), :,
i] = sol.y[V.pAKT, :]
self.simulations[self.obs_names.index("pS6K"), :,
i] = (sol.y[V.pS6K, :] * 83.8672192461257)
self.simulations[self.obs_names.index("pGSK3B"), :,
i] = (sol.y[V.pGSK3B, :] * 0.111097316860158)
self.simulations[self.obs_names.index("G6Pase"), :,
i] = (sol.y[V.G6Pase, :] * 0.0363622452066626)
def simulate(self, x, y0, _perturbation=None):
if _perturbation is not None:
self.perturbation = _perturbation
# get steady state
x[C.Ligand] = x[C.no_ligand] # No ligand
y0 = get_steady_state(self.diffeq, y0, tuple(x))
if not y0:
return False
# add ligand
for i, condition in enumerate(self.conditions):
if condition == "EGF":
x[C.Ligand] = x[C.EGF]
elif condition == "HRG":
x[C.Ligand] = x[C.HRG]
sol = solve_ode(self.diffeq, y0, self.t, tuple(x))
if sol is None:
return False
else:
self.simulations[
self.obs_names.index("Phosphorylated_MEKc"), :,
i] = sol.y[V.ppMEKc, :]
self.simulations[
self.obs_names.index("Phosphorylated_ERKc"), :,
i] = (sol.y[V.pERKc, :] + sol.y[V.ppERKc, :])
self.simulations[
self.obs_names.index("Phosphorylated_RSKw"), :,
i] = sol.y[V.pRSKc, :] + sol.y[V.pRSKn, :] * (x[C.Vn] /
x[C.Vc])
self.simulations[
self.obs_names.index("Phosphorylated_CREBw"), :,
i] = sol.y[V.pCREBn, :] * (x[C.Vn] / x[C.Vc])
self.simulations[self.obs_names.index("dusp_mRNA"), :,
i] = sol.y[V.duspmRNAc, :]
self.simulations[self.obs_names.index("cfos_mRNA"), :,
i] = sol.y[V.cfosmRNAc, :]
self.simulations[self.obs_names.index("cFos_Protein"), :,
i] = (
(sol.y[V.pcFOSn, :] + sol.y[V.cFOSn, :]) *
(x[C.Vn] / x[C.Vc]) + sol.y[V.cFOSc, :] +
sol.y[V.pcFOSc, :])
self.simulations[
self.obs_names.index("Phosphorylated_cFos"), :,
i] = (sol.y[V.pcFOSn, :] * (x[C.Vn] / x[C.Vc]) +
sol.y[V.pcFOSc, :])