Simulation example

In [1]:

    

from __future__ import print_function, division
%matplotlib inline


    

In [2]:

    

import tellurium as te
import phrasedml

# Get SBML from URN and set for phrasedml
urn = "urn:miriam:biomodels.db:BIOMD0000000012"
sbmlStr = te.temiriam.getSBMLFromBiomodelsURN(urn=urn)
phrasedml.setReferencedSBML(urn, sbmlStr)

# <SBML species>
#   PX - LacI protein
#   PY - TetR protein
#   PZ - cI protein
#   X - LacI mRNA
#   Y - TetR mRNA
#   Z - cI mRNA

# <SBML parameters>
#   ps_a - tps_active: Transcrition from free promotor in transcripts per second and promotor
#   ps_0 - tps_repr: Transcrition from fully repressed promotor in transcripts per second and promotor

phrasedmlStr = """
    model1 = model "{}"
    model2 = model model1 with ps_0=1.3E-5, ps_a=0.013
    sim1 = simulate uniform(0, 1000, 1000)
    task1 = run sim1 on model1
    task2 = run sim1 on model2

    # A simple timecourse simulation
    plot "Figure 1.1 Timecourse of repressilator" task1.time vs task1.PX, task1.PZ, task1.PY

    # Applying preprocessing
    plot "Figure 1.2 Timecourse after pre-processing" task2.time vs task2.PX, task2.PZ, task2.PY

    # Applying postprocessing
    plot "Figure 1.3 Timecourse after post-processing" task1.PX/max(task1.PX) vs task1.PZ/max(task1.PZ), \
                                                       task1.PY/max(task1.PY) vs task1.PX/max(task1.PX), \
                                                       task1.PZ/max(task1.PZ) vs task1.PY/max(task1.PY)
""".format(urn)


    

    




INFO:root:Initialising BioModels service (WSDL)

In [3]:

    

print(phrasedmlStr)


    

    




    model1 = model "urn:miriam:biomodels.db:BIOMD0000000012"
    model2 = model model1 with ps_0=1.3E-5, ps_a=0.013
    sim1 = simulate uniform(0, 1000, 1000)
    task1 = run sim1 on model1
    task2 = run sim1 on model2

    # A simple timecourse simulation
    plot "Figure 1.1 Timecourse of repressilator" task1.time vs task1.PX, task1.PZ, task1.PY

    # Applying preprocessing
    plot "Figure 1.2 Timecourse after pre-processing" task2.time vs task2.PX, task2.PZ, task2.PY

    # Applying postprocessing
    plot "Figure 1.3 Timecourse after post-processing" task1.PX/max(task1.PX) vs task1.PZ/max(task1.PZ),                                                        task1.PY/max(task1.PY) vs task1.PX/max(task1.PX),                                                        task1.PZ/max(task1.PZ) vs task1.PY/max(task1.PY)

In [ ]:

    

# convert to SED-ML
sedmlStr = phrasedml.convertString(phrasedmlStr)
if sedmlStr == None:
    print(phrasedml.getLastError())

# Run the SED-ML file with results written in workingDir
import tempfile
import shutil
workingDir = tempfile.mkdtemp(suffix="_sedml")


    

In [ ]:

    

te.executeSEDML(sedmlStr, workingDir=workingDir)
shutil.rmtree(workingDir)