def conditions_list(self, data_list): condnames = {} for d in data_list: condnames[d.con_name] = d.initials conditions = {k: ct.initial_conditions(v.keys(), v.values(), self.ic_params) for k, v in condnames.items()} return condnames, conditions
from anrm.irvin_anrm_bid_experiment_3 import model #-----------Simulator Settings-------------------------- sims = sim.Settings() sims.model = model sims.tspan = np.linspace(0,10000,100) #24hrs converted to seconds (1000 timepoints) sims.estimate_params = model.parameters_rules() sims.rtol = 1e-4 sims.atol = 1e-8 solve = sim.Solver(sims) solve.run() #-----------Initial Conditions-------------------------- ic_params = model.parameters_initial_conditions() conditions = ct.initial_conditions([], [], ic_params) ysim = solve.simulate(position = None, observables=True, initial_conc = conditions) yout = ct.extract_records(ysim, ['Obs_cPARP', 'Obs_MLKL']) PARP_MLKL_signals = yout td_PARP = ct.calculate_time_delay(PARP_MLKL_signals[:,0], sims.tspan) td_MLKL = ct.calculate_time_delay(PARP_MLKL_signals[:,1], sims.tspan) print td_PARP, td_MLKL p.ion() p.plot(sims.tspan, yout[:,0], label = 'Cleaved Parp') p.plot(sims.tspan, yout[:,1], label = 'MLKL') p.xlabel('time [sec]') p.ylabel('PARP and MLKL concentration [molecules per cell]')
import calibratortools as ct import simulator_1_0 as sim from pysb.integrate import odesolve from anrm.irvin_anrm_bid_experiment_0 import model #-----------Simulator Settings-------------------------- sims = sim.Settings() sims.model = model sims.tspan = np.linspace(0,86400,1000) #24hrs converted to seconds (1000 timepoints) sims.estimate_params = model.parameters_rules() sims.rtol = 1e-3 sims.atol = 1e-6 solve = sim.Solver(sims) solve.run() #-----------Initial Conditions-------------------------- ic_params = model.parameters_initial_conditions() conditions = ct.initial_conditions(['Bak_0', 'Bax_0', 'Bid_0'], [0, 0, 0], ic_params) ysim = solve.simulate(position = None, observables=True, initial_conc = conditions) yout = ct.extract_records(ysim, ['Obs_cPARP', 'Obs_MLKL']) p.ion() p.plot(sims.tspan, yout[:,0], label = 'Cleaved Parp') p.plot(sims.tspan, yout[:,1], label = 'MLKL') p.xlabel('time [sec]') p.ylabel('PARP and MLKL concentration [molecules per cell]') p.legend()
from pysb.integrate import odesolve #-----------Calibrated Parameters----------------------- position = pickle.load(open('CompII_Hypthesis_123_addeddata_4run_v41_Position.pkl')) #-----------Simulator Settings-------------------------- sims = sim.Settings() sims.model = model sims.tspan = np.linspace(0,20000,1000) sims.estimate_params = model.parameters_rules() sims.rtol = 1e-3 sims.atol = 1e-6 solve = sim.Solver(sims) solve.run() #-----------Initial Conditions-------------------------- ic_params = model.parameters_initial_conditions() conditions = ct.initial_conditions(['Bak_0', 'Bax_0', 'Bid_0', 'zVad_0'], [0.2e5, 40165, 0, 0], ic_params) #20uM zVad == 9.6e6 zVad per cell for a cell volume of 8e-13m3 ysim = solve.simulate(position, observables=True, initial_conc = conditions) yout = ct.extract_records(ysim, ['Obs_cPARP', 'Obs_MLKL','Obs_TNFa','Obs_NFkB', 'ComplexI','ComplexI_ub', 'ComplexI_TRAF', 'TRADD_RIP1', 'TRADD_RIP1_2','Obs_FADD_Sole', 'ComplexII','Bid_Trunc', 'Bid_PO4','Obs_RIP1', 'RIP1_Trunc', 'RIP3_Trunc', 'Necrosome','Obs_proC8', 'Obs_C8', 'Obs_C3ub', 'Obs_C3', 'Obs_pC3', 'RIP1_FADD','Obs_cPARP', 'Obs_PARP', 'Obs_MLKL','Obs_CytoC']) p.ion() p.plot(sims.tspan, yout[:,0], label = 'Cleaved Parp') p.plot(sims.tspan, yout[:,1], label = 'MLKL') p.xlabel('time [sec]') p.ylabel('PARP and MLKL concentration [molecules per cell]') p.legend()
#-----------Simulator Settings-------------------------- sims = sim.Settings() sims.model = model sims.tspan = np.linspace(0, 10000, 100) #24hrs converted to seconds (1000 timepoints) sims.estimate_params = model.parameters_rules() sims.rtol = 1e-4 sims.atol = 1e-8 solve = sim.Solver(sims) solve.run() #-----------Initial Conditions-------------------------- ic_params = model.parameters_initial_conditions() conditions = ct.initial_conditions([], [], ic_params) ysim = solve.simulate(position=None, observables=True, initial_conc=conditions) yout = ct.extract_records(ysim, ['Obs_cPARP', 'Obs_MLKL']) PARP_MLKL_signals = yout td_PARP = ct.calculate_time_delay(PARP_MLKL_signals[:, 0], sims.tspan) td_MLKL = ct.calculate_time_delay(PARP_MLKL_signals[:, 1], sims.tspan) print td_PARP, td_MLKL p.ion() p.plot(sims.tspan, yout[:, 0], label='Cleaved Parp') p.plot(sims.tspan, yout[:, 1], label='MLKL') p.xlabel('time [sec]') p.ylabel('PARP and MLKL concentration [molecules per cell]')
open('CompII_Hypthesis_123_addeddata_4run_v23_Position.pkl')) #-----------Simulator Settings-------------------------- sims = sim.Settings() sims.model = model sims.tspan = np.linspace(0, 20000, 1000) sims.estimate_params = model.parameters_rules() sims.rtol = 1e-3 sims.atol = 1e-6 solve = sim.Solver(sims) solve.run() #-----------Initial Conditions-------------------------- ic_params = model.parameters_initial_conditions() conditions = ct.initial_conditions(['Bak_0', 'Bax_0', 'Bid_0', 'zVad_0'], [0.2e5, 40165, 12044, 9.6e6], ic_params) #20uM zVad == 9.6e6 zVad per cell for a cell volume of 8e-13m3 ysim = solve.simulate(position, observables=True, initial_conc=conditions) yout = ct.extract_records(ysim, [ 'Obs_cPARP', 'Obs_MLKL', 'Obs_TNFa', 'Obs_NFkB', 'ComplexI', 'ComplexI_ub', 'ComplexI_TRAF', 'TRADD_RIP1', 'TRADD_RIP1_2', 'Obs_FADD_Sole', 'ComplexII', 'Bid_Trunc', 'Bid_PO4', 'Obs_RIP1', 'RIP1_Trunc', 'RIP3_Trunc', 'Necrosome', 'Obs_proC8', 'Obs_C8', 'Obs_C3ub', 'Obs_C3', 'Obs_pC3', 'RIP1_FADD', 'Obs_cPARP', 'Obs_PARP', 'Obs_MLKL', 'Obs_CytoC' ]) p.ion() p.plot(sims.tspan, yout[:, 0], label='Cleaved Parp') p.plot(sims.tspan, yout[:, 1], label='MLKL')
from pysb.integrate import odesolve from anrm.irvin_anrm_bid_experiment_0 import model #-----------Simulator Settings-------------------------- sims = sim.Settings() sims.model = model sims.tspan = np.linspace(0, 86400, 1000) #24hrs converted to seconds (1000 timepoints) sims.estimate_params = model.parameters_rules() sims.rtol = 1e-3 sims.atol = 1e-6 solve = sim.Solver(sims) solve.run() #-----------Initial Conditions-------------------------- ic_params = model.parameters_initial_conditions() conditions = ct.initial_conditions(['Bak_0', 'Bax_0', 'Bid_0'], [0, 0, 0], ic_params) ysim = solve.simulate(position=None, observables=True, initial_conc=conditions) yout = ct.extract_records(ysim, ['Obs_cPARP', 'Obs_MLKL']) p.ion() p.plot(sims.tspan, yout[:, 0], label='Cleaved Parp') p.plot(sims.tspan, yout[:, 1], label='MLKL') p.xlabel('time [sec]') p.ylabel('PARP and MLKL concentration [molecules per cell]') p.legend()
solve = sim.Solver(sims) solve.run() delta_td = [] apopt_td = [] necro_td = [] condition_variable = 'RIP1_0' graph_name = 'RIP1' rangecv = range_RIP1 for i in rangecv: #-----------Initial Conditions-------------------------- ic_params = model.parameters_initial_conditions() conditions = ct.initial_conditions([condition_variable], [i], ic_params) ysim = solve.simulate(position = position, observables=True, initial_conc = conditions) #-----------Calculate Time Delays----------------------- PARP_MLKL_signals = ct.extract_records(ysim, ['Obs_cPARP', 'Obs_MLKL']) td_PARP = ct.calculate_time_delay(PARP_MLKL_signals[:,0], sims.tspan) td_MLKL = ct.calculate_time_delay(PARP_MLKL_signals[:,1], sims.tspan) #-----------Time Delay vs. procaspase 8----------------- if (td_PARP is not None) & (td_MLKL is not None): delta_td.append(td_MLKL[0] - td_PARP[0]) apopt_td.append(td_PARP[0]) necro_td.append(td_MLKL[0]) #------------Plot Results-------------------------------- pl.ion()
#----Data and conditions---- ydata = ydata_fn() #init_conc = {'Apop1':{'TNFa_0': 600}} init_conc = {'Apop1':{'TNFa_0': 600}, 'Apop2':{'TNFa_0': 1200}, 'Necr1':{'TNFa_0':1800, 'zVad_0':9.6e6, 'FADD_0':0}} #600 = 10ng/ml TNFa, 9.6e6 = 20uM #----Normalize-------------- ynorm = ydata.copy() normalize = ct.normalize_array for k in ynorm.keys(): ynorm[k] = [normalize(ynorm[k][0], option = 1), ynorm[k][1]] #----Initial Protein Concetrations---- conditions = {} ic_params = model.parameters_initial_conditions() for k in init_conc.keys(): conditions[k] = ct.initial_conditions(init_conc[k].keys(), init_conc[k].values(), ic_params) #----Simulator Settings---- sims = sim.Settings() sims.model = model sims.tspan = np.linspace(0,36000,1000) #10hrs converted to seconds (1000 timepoints) sims.estimate_params = model.parameters_rules() sims.rtol = 1e-5 sims.atol = 1e-5 solve = sim.Solver(sims) solve.run() #----Bayesian and MCMC Options----
from pysb.integrate import odesolve #-----------Calibrated Parameters----------------------- position = pickle.load(open('CompII_Hypthesis_123_addeddata_4run_v23_Position.pkl')) #-----------Simulator Settings-------------------------- sims = sim.Settings() sims.model = model sims.tspan = np.linspace(0,20000,1000) sims.estimate_params = model.parameters_rules() sims.rtol = 1e-3 sims.atol = 1e-6 solve = sim.Solver(sims) solve.run() #-----------Initial Conditions-------------------------- ic_params = model.parameters_initial_conditions() conditions = ct.initial_conditions(['Bak_0', 'Bax_0', 'Bid_0', 'zVad_0'], [0.2e5, 40165, 12044, 9.6e6], ic_params) #20uM zVad == 9.6e6 zVad per cell for a cell volume of 8e-13m3 ysim = solve.simulate(position, observables=True, initial_conc = conditions) yout = ct.extract_records(ysim, ['Obs_cPARP', 'Obs_MLKL','Obs_TNFa','Obs_NFkB', 'ComplexI','ComplexI_ub', 'ComplexI_TRAF', 'TRADD_RIP1', 'TRADD_RIP1_2','Obs_FADD_Sole', 'ComplexII','Bid_Trunc', 'Bid_PO4','Obs_RIP1', 'RIP1_Trunc', 'RIP3_Trunc', 'Necrosome','Obs_proC8', 'Obs_C8', 'Obs_C3ub', 'Obs_C3', 'Obs_pC3', 'RIP1_FADD','Obs_cPARP', 'Obs_PARP', 'Obs_MLKL','Obs_CytoC']) p.ion() p.plot(sims.tspan, yout[:,0], label = 'Cleaved Parp') p.plot(sims.tspan, yout[:,1], label = 'MLKL') p.xlabel('time [sec]') p.ylabel('PARP and MLKL concentration [molecules per cell]') p.legend()
}, 'Apop2': { 'TNFa_0': 1200 }, 'Necr1': { 'TNFa_0': 1800, 'zVad_0': 9.6e6, 'FADD_0': 0 }, 'BidKO': { 'Bid_0': 0 } } ic_params = model.parameters_initial_conditions() for k in init_conc.keys(): conditions[k] = ct.initial_conditions(init_conc[k].keys(), init_conc[k].values(), ic_params) #----Simulator Settings---- sims = sim.Settings() sims.model = model sims.tspan = np.linspace(0, 36000, 1000) #10hrs converted to seconds (1000 timepoints) sims.estimate_params = model.parameters_rules() sims.rtol = 1e-5 sims.atol = 1e-5 solve = sim.Solver(sims) solve.run() #----Bayesian and MCMC Options---- opts = bmc.MCMCOpts()