def make_model(text):
"""Given text, return an INDRA model."""
from indra.assemblers import PysbAssembler
pa = PysbAssembler()
pa.add_statements(make_statements(text))
model = pa.make_model(policies='two_step')
return model
def make_model(text):
"""Given text, return an INDRA model."""
from indra.assemblers import PysbAssembler
pa = PysbAssembler()
pa.add_statements(make_statements(text))
model = pa.make_model(policies='two_step')
return model
def test_pysb_assembler_actsub():
stmt = ActiveForm(Agent("BRAF", mutations=[MutCondition("600", "V", "E")]), "activity", True)
pa = PysbAssembler()
pa.add_statements([stmt])
model = pa.make_model(policies="two_step")
assert len(model.rules) == 0
assert len(model.monomers) == 1
def test_pysb_assembler_autophos1():
enz = Agent("MEK1")
stmt = Autophosphorylation(enz, "serine", "222")
pa = PysbAssembler()
pa.add_statements([stmt])
model = pa.make_model()
assert len(model.rules) == 1
assert len(model.monomers) == 1
def get_model_checker(statements):
pa = PysbAssembler()
pa.add_statements(statements)
model = pa.make_model()
stmt = Influence(Concept('crop_production'), Concept('food_security'))
mc = ModelChecker(model, [stmt])
mc.prune_influence_map()
return mc
def test_pysb_assembler_dephos_noenz():
enz = None
sub = Agent("MEK1")
stmt = Phosphorylation(enz, sub, "serine", "222")
pa = PysbAssembler()
pa.add_statements([stmt])
model = pa.make_model()
assert len(model.rules) == 0
assert len(model.monomers) == 0
def test_pysb_assembler_complex1():
member1 = Agent("BRAF")
member2 = Agent("MEK1")
stmt = Complex([member1, member2])
pa = PysbAssembler()
pa.add_statements([stmt])
model = pa.make_model()
assert len(model.rules) == 2
assert len(model.monomers) == 2
def test_pysb_assembler_rasgap1():
gap = Agent("NF1")
ras = Agent("HRAS")
stmt = RasGap(gap, "catalytic", ras)
pa = PysbAssembler()
pa.add_statements([stmt])
model = pa.make_model()
print model.rules
assert len(model.rules) == 1
assert len(model.monomers) == 2
def test_pysb_assembler_phos_twostep_local():
enz = Agent("BRAF")
sub = Agent("MEK1")
stmt = Phosphorylation(enz, sub, "serine", "222")
pa = PysbAssembler()
pa.add_statements([stmt])
model = pa.make_model(policies="two_step")
print model.rules
assert len(model.rules) == 3
assert len(model.monomers) == 2
def test_pysb_assembler_autophos2():
raf1 = Agent("RAF1")
enz = Agent("MEK1", bound_conditions=[BoundCondition(raf1, True)])
stmt = Autophosphorylation(enz, "serine", "222")
pa = PysbAssembler()
pa.add_statements([stmt])
model = pa.make_model()
print model.rules
assert len(model.rules) == 1
assert len(model.monomers) == 2
def test_activity_activity():
subj = Agent("KRAS")
obj = Agent("BRAF")
stmt = Activation(subj, "activity", obj, "activity", True)
pa = PysbAssembler(policies="interactions_only")
pa.add_statements([stmt])
model = pa.make_model()
print model.rules
assert len(model.rules) == 1
assert len(model.monomers) == 2
def test_pysb_assembler_complex_multiway():
member1 = Agent("BRAF")
member2 = Agent("MEK1")
member3 = Agent("ERK1")
stmt = Complex([member1, member2, member3])
pa = PysbAssembler()
pa.add_statements([stmt])
model = pa.make_model(policies="multi_way")
assert len(model.rules) == 1
assert len(model.monomers) == 3
def test_pysb_assembler_dephos_twostep1():
phos = Agent("PP2A")
sub = Agent("MEK1")
stmt = Dephosphorylation(phos, sub, "serine", "222")
pa = PysbAssembler(policies="two_step")
pa.add_statements([stmt])
model = pa.make_model()
print model.rules
assert len(model.rules) == 3
assert len(model.monomers) == 2
def test_pysb_assembler_transphos1():
egfr = Agent("EGFR")
enz = Agent("EGFR", bound_conditions=[BoundCondition(egfr, True)])
stmt = Transphosphorylation(enz, "tyrosine")
pa = PysbAssembler()
pa.add_statements([stmt])
model = pa.make_model()
print model.rules
assert len(model.rules) == 1
assert len(model.monomers) == 1
def test_pysb_assembler_twostep_mixed():
member1 = Agent("BRAF")
member2 = Agent("RAF1")
st1 = Complex([member1, member2])
st2 = Phosphorylation(Agent("MAP2K1"), Agent("MAPK3"))
pa = PysbAssembler()
pa.add_statements([st1, st2])
pa.make_model(policies="two_step")
assert len(pa.model.rules) == 5
assert len(pa.model.monomers) == 4
def test_pysb_assembler_phos2():
hras = Agent("HRAS")
enz = Agent("BRAF", bound_conditions=[BoundCondition(hras, True)])
sub = Agent("MEK1")
stmt = Phosphorylation(enz, sub, "serine", "222")
pa = PysbAssembler()
pa.add_statements([stmt])
model = pa.make_model()
assert len(model.rules) == 1
assert len(model.monomers) == 3
def test_activity_activity3():
subj = Agent("Vemurafenib")
obj = Agent("BRAF")
stmt = Activation(subj, None, obj, "activity", False)
pa = PysbAssembler(policies="one_step")
pa.add_statements([stmt])
model = pa.make_model()
print model.rules
assert len(model.rules) == 1
assert len(model.monomers) == 2
def make_sbgn(pysb_model, model_id):
pa = PysbAssembler()
pa.model = pysb_model
for m in pysb_model.monomers:
pysb_assembler.set_extended_initial_condition(pysb_model, m, 0)
try:
sbgn_str = pa.export_model('sbgn')
except BngInterfaceError:
logger.error('Reaction network could not be generated for SBGN.')
return None
return sbgn_str
def test_pysb_assembler_act1():
egfr = Agent("EGFR")
subj = Agent("GRB2", bound_conditions=[BoundCondition(egfr, True)])
obj = Agent("SOS1")
stmt = Activation(subj, "activity", obj, "activity", True)
pa = PysbAssembler()
pa.add_statements([stmt])
model = pa.make_model()
print model.rules
assert len(model.rules) == 1
assert len(model.monomers) == 3
def test_mut():
mut = MutCondition("600", "V", "E")
st = Phosphorylation(Agent("BRAF", mutations=[mut]), Agent("MEK"))
pa = PysbAssembler()
pa.add_statements([st])
pa.make_model()
assert len(pa.model.rules) == 1
r = pa.model.rules[0]
braf = r.reactant_pattern.complex_patterns[0].monomer_patterns[0]
assert braf.monomer.name == "BRAF"
assert braf.site_conditions == {"V600": "E"}
def test_neg_agent_mod():
mc = ModCondition("phosphorylation", "serine", "123", False)
st = Phosphorylation(Agent("BRAF", mods=[mc]), Agent("MAP2K2"))
pa = PysbAssembler(policies="one_step")
pa.add_statements([st])
pa.make_model()
assert len(pa.model.rules) == 1
r = pa.model.rules[0]
braf = r.reactant_pattern.complex_patterns[0].monomer_patterns[0]
assert braf.monomer.name == "BRAF"
assert braf.site_conditions == {"S123": "u"}
def test_pysb_assembler_complex3():
hras = Agent("HRAS")
member1 = Agent("BRAF", bound_conditions=[BoundCondition(hras, True)])
member2 = Agent("MEK1")
stmt = Complex([member1, member2])
pa = PysbAssembler()
pa.add_statements([stmt])
model = pa.make_model()
print model.rules
assert len(model.rules) == 2
assert len(model.monomers) == 3
def test_pysb_assembler_dephos2():
phos = Agent("PP2A")
raf1 = Agent("RAF1")
sub = Agent("MEK1", bound_conditions=[BoundCondition(raf1, True)])
stmt = Dephosphorylation(phos, sub, "serine", "222")
pa = PysbAssembler()
pa.add_statements([stmt])
model = pa.make_model()
print model.rules
assert len(model.rules) == 1
assert len(model.monomers) == 3
def test_pysb_assembler_phos_twostep_local_to_global():
enz = Agent("BRAF")
sub = Agent("MEK1")
stmt = Phosphorylation(enz, sub, "serine", "222")
pa = PysbAssembler()
pa.add_statements([stmt])
model = pa.make_model(policies="two_step")
# This call should have reverted to default policy
model = pa.make_model()
print model.rules
assert len(model.rules) == 1
assert len(model.monomers) == 2
def test_grounded_active_pattern():
a = Agent('A', db_refs={'HGNC': '1234'})
b = Agent('B', db_refs={'HGNC': '5678'})
b_phos = Agent('B', mods=[ModCondition('phosphorylation', 'S', '100')],
db_refs={'HGNC': '5678'})
b_act = Agent('B', activity=ActivityCondition('activity', True),
db_refs={'HGNC': '5678'})
st1 = Phosphorylation(a, b, 'S', '100')
st2 = ActiveForm(b_phos, 'activity', True)
pysba = PysbAssembler(policies='one_step')
pysba.add_statements([st1, st2])
model = pysba.make_model()
mps = list(pa.grounded_monomer_patterns(model, b_act))
def test_unspecified_statement_policies():
enz = Agent("BRAF")
sub = Agent("MEK1")
phos = Agent("PP2A")
stmt1 = Phosphorylation(enz, sub, "serine", "222")
stmt2 = Dephosphorylation(phos, sub, "serine", "222")
policies = {"Phosphorylation": "two_step", "other": "interactions_only"}
pa = PysbAssembler(policies=policies)
pa.add_statements([stmt1, stmt2])
model = pa.make_model()
print model.rules
assert len(model.rules) == 4
assert len(model.monomers) == 3
def test_pysb_assembler_actmod2():
mek = Agent("MEK")
erk = Agent("ERK")
stmts = []
stmts.append(ActiveForm(Agent("MEK", mods=[ModCondition("phosphorylation", "serine", "218")]), "activity", True))
stmts.append(ActiveForm(Agent("MEK", mods=[ModCondition("phosphorylation", "serine", "222")]), "activity", True))
stmts.append(Phosphorylation(mek, erk, "threonine", "185"))
stmts.append(Phosphorylation(mek, erk, "tyrosine", "187"))
pa = PysbAssembler()
pa.add_statements(stmts)
model = pa.make_model()
print model.rules
assert len(model.rules) == 4
assert len(model.monomers) == 2
def assemble_pysb(stmts, data_genes, out_file):
"""Return an assembled PySB model."""
base_file, _ = os.path.splitext(out_file)
#stmts = ac.load_statements('%s.pkl' % base_file)
stmts = preprocess_stmts(stmts, data_genes)
# This is the "final" set of statements going into the assembler so it
# makes sense to cache these.
# This is also the point where index cards can be generated
ac.dump_statements(stmts, '%s_before_pa.pkl' % base_file)
assemble_index_cards(stmts, 'output/index_cards')
# Save a version of statements with no evidence for faster loading
for s in stmts:
s.evidence = []
for ss in s.supports + s.supported_by:
ss.evidence = []
ac.dump_statements(stmts, '%s_no_evidence.pkl' % base_file)
# Assemble model
pa = PysbAssembler()
pa.add_statements(stmts)
pa.make_model(reverse_effects=False)
#ac.dump_statements(pa.statements, '%s_after_pa.pkl' % base_file)
# Set context
set_context(pa)
# Add observables
add_observables(pa.model)
pa.save_model(out_file)
with open('korkut_pysb.pkl', 'wb') as fh:
pickle.dump(pa.model, fh)
#pa.export_model('kappa', '%s.ka' % base_file)
return pa.model
def test_act_michaelis_menten():
stmt = Activation(Agent('MEK'), Agent('ERK'))
stmt2 = Inhibition(Agent('DUSP'), Agent('ERK'))
pa = PysbAssembler()
pa.add_statements([stmt, stmt2])
pa.make_model(policies='michaelis_menten')
assert(len(pa.model.parameters) == 7)
def test_missing_catalytic_default_site():
c8 = Agent('CASP8', activity=ActivityCondition('catalytic', True))
c3 = Agent('CASP3')
stmt = Activation(c8, c3, 'catalytic')
# Interactions only
pa = PysbAssembler(policies='interactions_only')
pa.add_statements([stmt])
model = pa.make_model()
# One step
pa = PysbAssembler(policies='one_step')
pa.add_statements([stmt])
model = pa.make_model()
# Two step
pa = PysbAssembler(policies='two_step')
pa.add_statements([stmt])
model = pa.make_model()
def test_missing_transcription_default_site():
p53 = Agent('TP53', activity=ActivityCondition('transcription', True))
bax = Agent('BAX')
stmt = Activation(p53, bax)
# Interactions only
pa = PysbAssembler(policies='interactions_only')
pa.add_statements([stmt])
model = pa.make_model()
# One step
pa = PysbAssembler(policies='one_step')
pa.add_statements([stmt])
model = pa.make_model()
# Two step
pa = PysbAssembler(policies='two_step')
pa.add_statements([stmt])
model = pa.make_model()
def test_increaseamount_hill():
stmt = IncreaseAmount(Agent('TP53'), Agent('MDM2'))
pa = PysbAssembler()
pa.add_statements([stmt])
pa.make_model(policies='hill')
pa.save_model()
assert(len(pa.model.parameters) == 5)
def test_annotation():
st = Phosphorylation(Agent('BRAF', db_refs = {'UP': 'P15056'}),
Agent('MAP2K2', db_refs = {'HGNC': '6842'}))
pa = PysbAssembler()
pa.add_statements([st])
pa.make_model()
assert(len(pa.model.annotations) == 5)
def remove_kappa_dead_rules(stmts, model, dead_rules):
# FIXME: we should probably check that a statement we remove has all its
# generated rules recognized as dead. If it has at least one live rule
# coming from it, we shouldn't remove it. But the dead rules should still
# be removed somehow from the final model.
dead_uuids = set()
for rule in dead_rules:
for ann in model.annotations:
if ann.subject == rule and ann.predicate == 'from_indra_statement':
dead_uuids.add(ann.object)
all_uuids = {stmt.uuid for stmt in stmts}
live_uuids = all_uuids - dead_uuids
stmts = ac.filter_uuid_list(stmts, live_uuids)
pa = PysbAssembler()
pa.add_statements(stmts)
model = pa.make_model()
return stmts, model
def test_pysb_assembler_autophos1():
enz = Agent('MEK1')
stmt = Autophosphorylation(enz, 'serine', '222')
pa = PysbAssembler()
pa.add_statements([stmt])
model = pa.make_model()
assert(len(model.rules)==1)
assert(len(model.monomers)==1)
def test_pysb_assembler_actsub():
stmt = ActiveForm(Agent('BRAF', mutations=[MutCondition('600', 'V', 'E')]),
'activity', True)
pa = PysbAssembler()
pa.add_statements([stmt])
model = pa.make_model(policies='two_step')
assert(len(model.rules)==0)
assert(len(model.monomers)==1)
def test_convert_subj():
stmt = Conversion(Agent('PIK3CA'), [Agent('PIP2')], [Agent('PIP3')])
pa = PysbAssembler()
pa.add_statements([stmt])
pa.make_model()
assert(len(pa.model.parameters) == 4)
assert(len(pa.model.rules) == 1)
assert(len(pa.model.monomers) == 3)
def replace_agent(self, agent_name, agent_replacement_names, model_id):
"""Replace an agent in a model with other agents.
This is used, for instance, to expand a protein family to
multiple specific proteins.
"""
for stmt in self.statements[model_id - 1]:
agent_key = [
i for i, m in enumerate(stmt.agent_list())
if m is not None and m.name == agent_name
]
if agent_key:
self.statements[model_id - 1].remove(stmt)
for p in agent_replacement_names:
s = copy.deepcopy(stmt)
if isinstance(stmt, Complex):
s.members[agent_key[0]].name = p
else:
s.__dict__[agent_key[0]].name = p
self.extend_statements([s], model_id)
pa = PysbAssembler()
pa.add_statements(self.statements[model_id - 1])
model = pa.make_model()
pa.add_default_initial_conditions(self.default_initial_amount)
return model
def assemble_model(stmts):
pa = PysbAssembler(policies='one_step')
pa.add_statements(stmts)
model = pa.make_model()
pa.add_default_initial_conditions(100.0)
try:
targeted_agents = get_targeted_agents(stmts)
no_upstream_active_agents = get_no_upstream_active_agents(stmts)
except:
targeted_agents = []
no_upstream_active_agents = []
try:
chemical_agents = get_chemical_agents(stmts)
except:
chemical_agents = []
for m in model.monomers:
try:
if m.name in targeted_agents or m.name in no_upstream_active_agents:
pysb_assembler.set_base_initial_condition(model,
model.monomers[m.name], 50.0)
pysb_assembler.set_extended_initial_condition(model, m, 50.0)
elif m.name in chemical_agents:
pysb_assembler.set_base_initial_condition(model,
model.monomers[m.name], 10000.0)
else:
pysb_assembler.set_extended_initial_condition(model, m, 0)
except:
pysb_assembler.set_extended_initial_condition(model, m, 0)
# Tweak parameters
for param in model.parameters:
if 'kf' in param.name and 'bind' in param.name:
param.value = param.value * 100
return model
def test_pysb_assembler_complex_twostep():
member1 = Agent('BRAF')
member2 = Agent('MEK1')
stmt = Complex([member1, member2])
pa = PysbAssembler()
pa.add_statements([stmt])
model = pa.make_model(policies='two_step')
assert(len(model.rules)==2)
assert(len(model.monomers)==2)
def test_activity_activity3():
subj = Agent('Vemurafenib')
obj = Agent('BRAF')
stmt = Inhibition(subj, obj)
pa = PysbAssembler(policies='one_step')
pa.add_statements([stmt])
model = pa.make_model()
assert(len(model.rules)==1)
assert(len(model.monomers)==2)
def test_activity_activity():
subj = Agent('KRAS')
obj = Agent('BRAF')
stmt = Activation(subj, obj)
pa = PysbAssembler(policies='interactions_only')
pa.add_statements([stmt])
model = pa.make_model()
assert(len(model.rules)==1)
assert(len(model.monomers)==2)
def test_pysb_assembler_dephos_twostep1():
phos = Agent('PP2A')
sub = Agent('MEK1')
stmt = Dephosphorylation(phos, sub, 'serine', '222')
pa = PysbAssembler(policies='two_step')
pa.add_statements([stmt])
model = pa.make_model()
assert(len(model.rules)==3)
assert(len(model.monomers)==2)
def test_pysb_assembler_phos_twostep_local():
enz = Agent('BRAF')
sub = Agent('MEK1')
stmt = Phosphorylation(enz, sub, 'serine', '222')
pa = PysbAssembler()
pa.add_statements([stmt])
model = pa.make_model(policies='two_step')
assert(len(model.rules)==3)
assert(len(model.monomers)==2)
def test_pysb_assembler_transphos1():
egfr = Agent('EGFR')
enz = Agent('EGFR', bound_conditions=[BoundCondition(egfr, True)])
stmt = Transphosphorylation(enz, 'tyrosine')
pa = PysbAssembler()
pa.add_statements([stmt])
model = pa.make_model()
assert(len(model.rules)==1)
assert(len(model.monomers)==1)
def test_pysb_assembler_autophos2():
raf1 = Agent('RAF1')
enz = Agent('MEK1', bound_conditions=[BoundCondition(raf1, True)])
stmt = Autophosphorylation(enz, 'serine', '222')
pa = PysbAssembler()
pa.add_statements([stmt])
model = pa.make_model()
assert(len(model.rules)==1)
assert(len(model.monomers)==2)
def test_annotation_regamount():
st1 = IncreaseAmount(Agent('BRAF', db_refs = {'UP': 'P15056'}),
Agent('MAP2K2', db_refs = {'HGNC': '6842'}))
st2 = DecreaseAmount(Agent('BRAF', db_refs = {'UP': 'P15056'}),
Agent('MAP2K2', db_refs = {'HGNC': '6842'}))
pa = PysbAssembler()
pa.add_statements([st1, st2])
pa.make_model()
assert(len(pa.model.annotations) == 8)
def test_pysb_assembler_dephos_noenz():
enz = None
sub = Agent('MEK1')
stmt = Phosphorylation(enz, sub, 'serine', '222')
pa = PysbAssembler()
pa.add_statements([stmt])
model = pa.make_model()
assert(len(model.rules)==0)
assert(len(model.monomers)==0)
def test_non_python_name_phos():
st = Phosphorylation(Agent('14-3-3'), Agent('BRAF kinase'))
pa = PysbAssembler()
pa.add_statements([st])
pa.make_model()
names = [m.name for m in pa.model.monomers]
assert('BRAF_kinase' in names)
assert('p14_3_3' in names)
bng.generate_equations(pa.model)
def test_agent_loc():
st = Phosphorylation(Agent('BRAF', location='cytoplasm'), Agent('MEK'))
pa = PysbAssembler()
pa.add_statements([st])
pa.make_model()
assert(len(pa.model.rules) == 1)
r = pa.model.rules[0]
braf = r.reactant_pattern.complex_patterns[0].monomer_patterns[0]
assert(braf.site_conditions == {'loc': 'cytoplasm'})
def test_pysb_assembler_gap1():
gap = Agent('NF1')
ras = Agent('HRAS')
stmt = Gap(gap, ras)
pa = PysbAssembler()
pa.add_statements([stmt])
model = pa.make_model()
assert(len(model.rules)==1)
assert(len(model.monomers)==2)
def test_pysb_assembler_gef1():
gef = Agent('SOS1')
ras = Agent('HRAS')
stmt = Gef(gef, ras)
pa = PysbAssembler()
pa.add_statements([stmt])
model = pa.make_model()
assert(len(model.rules)==1)
assert(len(model.monomers)==2)
def test_activeform_site():
a = Agent('A', db_refs={'HGNC': '1234'})
b = Agent('B', db_refs={'HGNC': '5678'})
b_phos = Agent('B', mods=[ModCondition('phosphorylation', 'Y', '200')],
db_refs={'HGNC': '5678'})
st1 = Phosphorylation(a, b, 'S', '100')
st2 = ActiveForm(b_phos, 'kinase', True)
pa = PysbAssembler(policies='one_step')
pa.add_statements([st1, st2])
model = pa.make_model()
def test_set_context_monomer_notfound():
st = Phosphorylation(Agent("MAP2K1"), Agent("XYZ"))
pa = PysbAssembler()
pa.add_statements([st])
pa.make_model()
assert pa.model.parameters["MAP2K1_0"].value < 1000
assert pa.model.parameters["XYZ_0"].value < 1000
pa.set_context("A375_SKIN")
assert pa.model.parameters["MAP2K1_0"].value > 10000
assert pa.model.parameters["XYZ_0"].value < 1000
def get_subnetwork(statements, nodes, relevance_network=None,
relevance_node_lim=10):
"""Return a PySB model based on a subset of given INDRA Statements.
Statements are first filtered for nodes in the given list and other nodes
are optionally added based on relevance in a given network. The filtered
statements are then assembled into an executable model using INDRA's
PySB Assembler.
Parameters
----------
statements : list[indra.statements.Statement]
A list of INDRA Statements to extract a subnetwork from.
nodes : list[str]
The names of the nodes to extract the subnetwork for.
relevance_network : Optional[str]
The UUID of the NDEx network in which nodes relevant to the given
nodes are found.
relevance_node_lim : Optional[int]
The maximal number of additional nodes to add to the subnetwork
based on relevance.
Returns
-------
model : pysb.Model
A PySB model object assembled using INDRA's PySB Assembler from
the INDRA Statements corresponding to the subnetwork.
"""
if relevance_network is not None:
relevant_nodes = _find_relevant_nodes(nodes, relevance_network,
relevance_node_lim)
all_nodes = nodes + relevant_nodes
else:
all_nodes = nodes
filtered_statements = _filter_statements(statements, all_nodes)
pa = PysbAssembler()
pa.add_statements(filtered_statements)
model = pa.make_model()
return model
def assemble_pysb(stmts, data_genes, out_file):
"""Return an assembled PySB model."""
stmts = ac.filter_direct(stmts)
stmts = ac.filter_belief(stmts, 0.95)
stmts = ac.filter_top_level(stmts)
stmts = ac.filter_gene_list(stmts, data_genes, 'all')
stmts = ac.reduce_activities(stmts)
pa = PysbAssembler()
pa.add_statements(stmts)
model = pa.make_model()
# Add observables
o = Observable('MAPK1p', model.monomers['MAPK1'](T185='p', Y187='p'))
model.add_component(o)
o = Observable('MAPK3p', model.monomers['MAPK3'](T202='p', Y204='p'))
model.add_component(o)
o = Observable('GSK3Ap', model.monomers['GSK3A'](S21='p'))
model.add_component(o)
o = Observable('GSK3Bp', model.monomers['GSK3B'](S9='p'))
model.add_component(o)
o = Observable('RPS6p', model.monomers['RPS6'](S235='p'))
model.add_component(o)
o = Observable('EIF4EBP1p', model.monomers['EIF4EBP1'](S65='p'))
model.add_component(o)
o = Observable('JUNp', model.monomers['JUN'](S73='p'))
model.add_component(o)
o = Observable('FOXO3p', model.monomers['FOXO3'](S315='p'))
model.add_component(o)
o = Observable('AKT1p', model.monomers['AKT1'](S473='p'))
model.add_component(o)
o = Observable('AKT2p', model.monomers['AKT2'](S474='p'))
model.add_component(o)
o = Observable('AKT3p', model.monomers['AKT3'](S='p'))
model.add_component(o)
o = Observable('ELK1', model.monomers['ELK1'](S383='p'))
model.add_component(o)
# Set context
pa.set_context('SKMEL28_SKIN')
pa.save_model(out_file)
ke = KappaExporter(model)
with open('%s.ka' % base_file, 'wb') as fh:
base_file, _ = os.path.splitext(out_file)
fh.write(ke.export().encode('utf-8'))
return model
def test_save_rst():
st = Phosphorylation(Agent("MAP2K1"), Agent("MAPK3"))
pa = PysbAssembler()
pa.add_statements([st])
pa.make_model()
pa.save_rst("/dev/null")
def test_annotation():
st = Phosphorylation(Agent("BRAF", db_refs={"UP": "P15056"}), Agent("MAP2K2", db_refs={"HGNC": "6842"}))
pa = PysbAssembler()
pa.add_statements([st])
pa.make_model()
assert len(pa.model.annotations) == 2
from indra.util import plot_formatting as pf
from indra.assemblers import PysbAssembler
# 1. TEXT
# User defines text:
text = ('MEK1 phosphorylates ERK2 on threonine 185 and tyrosine 187.')
# Show round trip going out to TRIPS/DRUM web service,
# return logical form to INDRA, which is queried by
# INDRA for relevant statements
tp = trips.process_text(text)
# Now generate PySB model
stmts = tp.statements # Don't show this one
pa = PysbAssembler()
pa.add_statements(stmts)
pa.make_model()
t = np.linspace(0, 25000)
sol = Solver(pa.model, t)
sol.run()
pf.set_fig_params()
plt.ion()
plt.figure(figsize=(1, 1), dpi=300)
species_names = [str(s) for s in pa.model.species]
plt.plot(t, sol.y[:, species_names.index("MAPK1(T185='u', Y187='u')")],
'b', label='MAPK1.uu')
plt.plot(t, sol.y[:, species_names.index("MAPK1(T185='p', Y187='u')")] +
sol.y[:, species_names.index("MAPK1(T185='u', Y187='p')")],
'g', label='MAPK1.p')
else:
sdict[s]=None
return mon(sdict)
def add_initial(model, pattern, value):
"""Add initial condition; if an initial condition for this pattern
already exists, override it."""
complex_pattern = pysb.as_complex_pattern(pattern)
for other_cp, other_value in model.initial_conditions:
if complex_pattern.is_equivalent_to(other_cp):
model.initial_conditions.remove((other_cp, other_value))
model.initial(complex_pattern, value)
# Generate model rules via indra
pa = PysbAssembler()
bp = bel.process_belrdf('../../data/RAS_combined.rdf')
pa.add_statements(bp.statements)
model = pa.make_model(initial_conditions=False)
# Useful shortcuts to access model components
m = model.monomers
p = model.parameters
# Add ligand to the model
model.add_component(Monomer('EGF'))
model.add_component(Parameter('kf_ee_act', 1e-6))
model.add_component(
Rule('EGF_activates_EGFR',
m['EGF']() + m['EGFR']({'Kinase':'inactive'}) >>
m['EGF']() + m['EGFR']({'Kinase':'active'}),
