def test_standard_noInput(self):
fba = FluxBalanceAnalysis(**_testStandard)
self.assertEqual(fba.getBiomassReactionFlux(), 0)
for moleculeID, change in zip(fba.getOutputMoleculeIDs(),
fba.getOutputMoleculeLevelsChange()):
if moleculeID == "B":
self.assertAlmostEqual(0, change)
elif moleculeID == "C":
self.assertAlmostEqual(0, change)
elif moleculeID == "E":
self.assertAlmostEqual(0, change)
def testModel(toyModelReactionStoich=toyModelReactionStoich, biomassReactionStoich=biomassReactionStoich, transportLimits=transportLimits, reactionEnzymes=reactionEnzymes, enzymeConcentrations=enzymeConcentrations): fba = FluxBalanceAnalysis( reactionStoich=toyModelReactionStoich, externalExchangedMolecules=transportLimits.keys(), objective=biomassReactionStoich["v_biomass"], objectiveType="standard", solver="glpk", ) exchangeMolecules = fba.getExternalMoleculeIDs() fba.setExternalMoleculeLevels([transportLimits[molID] for molID in exchangeMolecules]) for reactionID in toyModelReactionStoich: if reactionID in reactionEnzymes: enzymeID = reactionEnzymes[reactionID] if enzymeID in enzymeConcentrations: fba.setMaxReactionFlux(reactionID, KCAT_MAX * enzymeConcentrations[enzymeID]) return fba.getBiomassReactionFlux()[0]
def test_standard(self):
fba = FluxBalanceAnalysis(**_testStandard)
externalMoleculeLevels = {"A": 50, "D": 20}
fba.setExternalMoleculeLevels([
externalMoleculeLevels[moleculeID]
for moleculeID in fba.getExternalMoleculeIDs()
])
self.assertEqual(fba.getBiomassReactionFlux(), 1.0)
for moleculeID, change in zip(fba.getOutputMoleculeIDs(),
fba.getOutputMoleculeLevelsChange()):
if moleculeID == "B":
self.assertAlmostEqual(10, change)
elif moleculeID == "C":
self.assertAlmostEqual(10, change)
elif moleculeID == "E":
self.assertAlmostEqual(20, change)
"ATP": 1
},
}
biomassReactionStoich = {"v_biomass": {"C": 1, "F": 1, "H": 1, "ATP": 10}}
transportLimits = {
"A": 21.0,
"F": 5.0,
"D": -12.0,
"E": -12.0,
"H": 5.0,
"O2": 15.0,
}
fba = FluxBalanceAnalysis(
reactionStoich=toyModelReactionStoich,
externalExchangedMolecules=transportLimits.keys(),
objective=biomassReactionStoich["v_biomass"],
objectiveType="standard",
solver="glpk",
)
exchangeMolecules = fba.getExternalMoleculeIDs()
fba.setExternalMoleculeLevels(
[transportLimits[molID] for molID in exchangeMolecules])
biomassReactionFlux = fba.getBiomassReactionFlux()[0]
print biomassReactionFlux
fba_moma.setExternalMoleculeLevels(
[transportLimits[molID] for molID in exchangeMolecules])
return fba_moma.errorFluxes(), fba_moma.errorAdjustedReactionFluxes()
fba = FluxBalanceAnalysis(
reactionStoich=toyModelReactionStoich,
externalExchangedMolecules=transportLimits.keys(),
objective=biomassReactionStoich["v_biomass"],
objectiveType="standard",
solver="glpk",
)
exchangeMolecules = fba.getExternalMoleculeIDs()
fba.setExternalMoleculeLevels(
[transportLimits[molID] for molID in exchangeMolecules])
wildtypeBiomassFlux = fba.getBiomassReactionFlux()
# Adjust kcats
targetFluxes = {}
for reactionID, enzymeID in reactionEnzymes.iteritems():
targetFluxes[
reactionID] = enzymeConcentrations[enzymeID] * enzymeKcats[enzymeID]
targetFluxes["v_biomass"] = wildtypeBiomassFlux
errors, rates = checkErrors(targetFluxes)
errors_dict = dict(zip(enzymeKcats, errors))
kcat_adjustments = {
enzymeID: error / enzymeConcentrations[enzymeID]
for enzymeID, error in errors_dict.iteritems()