def test_structure_to_negative_interaction_states() -> None:
rxncon_system = Quick("""Cdc28_P+_Bem2_[(cdc28)]; ! <Cdc28Cln13>
<Cdc28Cln13>; OR <Cdc28Cln1>; OR <Cdc28Cln3>
<Cdc28Cln1>; AND Cdc28_[cyclin]--Cln1_[cdc28]
<Cdc28Cln3>; AND Cdc28_[cyclin]--Cln3_[cdc28]; AND Cdc28_[whi3]--0
Cdc28_[cyclin]_ppi_Cln1_[cdc28]
Cdc28_[far1]_ppi_Far1_[cdc28]
Cdc28_[cks1]_ppi_Cks1_[cdc28]
Cak1_P+_Cdc28_[Tloop(T169)]
Cdc28_[cyclin]_ppi_Cln2_[cdc28]
Cdc28_[cyclin]_ppi_Cln3_[cdc28]
Cdc28_[whi3]_ppi_Whi3_[cdc28]""").rxncon_system
rbm = rule_based_model_from_rxncon(rxncon_system)
rules_of_interest = [
rule_from_str(
"Cdc28(whi3D) + Whi3(cdc28D) -> Cdc28(whi3D!1).Whi3(cdc28D!1) k_13 Cdc28_[whi3]_ppi+_Whi3_[cdc28]"),
rule_from_str(
"Cdc28(whi3D!1).Whi3(cdc28D!1) -> Cdc28(whi3D) + Whi3(cdc28D) k_14 Cdc28_[whi3]_ppi-_Whi3_[cdc28]")
]
for rule_of_interest in rules_of_interest:
identities = [rule.is_equivalent_to(rule_of_interest) for rule in rbm.rules]
assert identities.count(True) == 1 # exactly once
def test_trslprocat() -> None:
procatdef = reaction.ReactionDef(
'pro-cat-translation',
'$x_trslprocat_$y',
{
'$x': (Spec, LocusResolution.component),
'$y': (MRNASpec, LocusResolution.component)
},
'$x%# + $y%# -> $x%# + $y%# + $y.to_protein_component_spec().with_name_suffix(\'PRO\')%!$y.to_protein_component_spec().with_name_suffix(\'CAT\')%#' # pylint: disable=line-too-long
'$y.to_protein_component_spec().with_name_suffix(\'PRO\').with_domain(\'PROCAT\')%--$y.to_protein_component_spec().with_name_suffix(\'CAT\').with_domain(\'CATPRO\')%!0'
)
reaction.REACTION_DEFS = reaction.DEFAULT_REACTION_DEFS + [procatdef]
rxn_system = Quick("""Ribo_trslprocat_Ssy5mRNA
A_p+_Ssy5CAT
B_deg_Ssy5PRO""").rxncon_system
rbm = rule_based_model_from_rxncon(rxn_system)
expected_rules = [
'Ribo() + Ssy5mRNA() -> Ribo() + Ssy5CAT(AR~0,CATPROD!1).Ssy5PRO(PROCATD!1) + Ssy5mRNA() k',
'A() + Ssy5CAT(AR~0) -> A() + Ssy5CAT(AR~p) k',
'B() + Ssy5PRO() -> B() k'
]
assert len(rbm.rules) == len(expected_rules)
for actual_rule in rbm.rules:
assert any(rule_from_str(rule).is_equivalent_to(actual_rule) for rule in expected_rules)
reaction.REACTION_DEFS = reaction.DEFAULT_REACTION_DEFS
def test_boolean_inhibition_interaction() -> None:
rbm = rule_based_model_from_rxncon(Quick('''A_ppi+_C
C_ppi+_D
B_ppi+_E
B_ppi+_F
A_ppi+_B; x <comp1>
<comp1>; OR <comp1C1>
<comp1>; OR <comp2C1>
<comp1C1>; AND A--C
<comp1C1>; AND C--D
<comp2C1>; AND B--F
<comp2C1>; AND B--E''').rxncon_system)
expected_rules = [
'A(CD) + C(AD) -> A(CD!1).C(AD!1) k',
'C(DD) + D(CD) -> C(DD!1).D(CD!1) k',
'B(ED) + E(BD) -> B(ED!1).E(BD!1) k',
'B(FD) + F(BD) -> B(FD!1).F(BD!1) k',
'A(BD,CD) + B(AD,FD) -> A(BD!1,CD).B(AD!1,FD) k',
'A(BD,CD) + B(AD,ED,FD!1).F(BD!1) -> A(BD!2,CD).B(AD!2,ED,FD!1).F(BD!1) k',
'A(BD,CD!1).C(AD!1,DD) + B(AD,FD) -> A(BD!2,CD!1).B(AD!2,FD).C(AD!1,DD) k',
'A(BD,CD!1).C(AD!1,DD) + B(AD,ED,FD!2).F(BD!2) -> A(BD!3,CD!1).B(AD!3,ED,FD!2).C(AD!1,DD).F(BD!2) k',
]
assert len(rbm.rules) == len(expected_rules)
for actual_rule in rbm.rules:
assert any(rule_from_str(rule).is_equivalent_to(actual_rule) for rule in expected_rules)
def test_single_requirement_modification() -> None:
rbm = rule_based_model_from_rxncon(Quick("""A_[b]_ppi+_B_[a]; ! A_[(r)]-{p}
A_[b]_ppi-_B_[a]
C_p+_A_[(r)]
D_p-_A_[(r)]""").rxncon_system)
expected_rules = [
'A(rR~p,bD) + B(aD) -> A(rR~p,bD!1).B(aD!1) k',
'A(bD!1).B(aD!1) -> A(bD) + B(aD) k',
'C() + A(rR~0) -> C() + A(rR~p) k',
'A(rR~p) + D() -> A(rR~0) + D() k'
]
assert len(rbm.rules) == len(expected_rules)
for actual_rule in rbm.rules:
print(actual_rule)
# assert any(rule_from_str(rule).is_equivalent_to(actual_rule) for rule in expected_rules)
expected_ics = [
'A(bD,rR~0) NumA',
'B(aD) NumB',
'D() NumD',
'C() NumC'
]
for actual_ic in rbm.initial_conditions:
assert any(initial_condition_from_str(ic).is_equivalent_to(actual_ic) for ic in expected_ics)
def test_single_inhibition_interaction() -> None:
rbm = rule_based_model_from_rxncon(Quick("""A_[b]_ppi+_B_[a]; x A_[(r)]-{p}
E_[x]_ppi+_B_[a]
C_p+_A_[(r)]
D_ub+_A_[(r)]""").rxncon_system)
expected_rules = [
'A(rR~ub,bD) + B(aD) -> A(rR~ub,bD!1).B(aD!1) k',
'A(rR~0,bD) + B(aD) -> A(rR~0,bD!1).B(aD!1) k',
'B(aD) + E(xD) -> B(aD!1).E(xD!1) k',
'A(rR~0) + C() -> A(rR~p) + C() k',
'A(rR~0) + D() -> A(rR~ub) + D() k'
]
assert len(rbm.rules) == len(expected_rules)
for actual_rule in rbm.rules:
assert any(rule_from_str(rule).is_equivalent_to(actual_rule) for rule in expected_rules)
expected_ics = [
'A(bD,rR~0) NumA',
'B(aD) NumB',
'D() NumD',
'C() NumC',
'E(xD) NumE'
]
for actual_ic in rbm.initial_conditions:
assert any(initial_condition_from_str(ic).is_equivalent_to(actual_ic) for ic in expected_ics)
def write_bngl(excel_filename: str, base_name=None):
if not base_name:
base_name = os.path.splitext(os.path.basename(excel_filename))[0]
base_path = os.path.dirname(excel_filename)
bngl_model_filename = os.path.join(base_path, '{0}.bngl'.format(base_name))
print('Reading in Excel file [{}] ...'.format(excel_filename))
excel_book = ExcelBook(excel_filename)
rxncon_system = excel_book.rxncon_system
print(
'Constructed rxncon system: [{} reactions], [{} contingencies]'.format(
len(rxncon_system.reactions), len(rxncon_system.contingencies)))
print('Generating BNGL output ...')
rbm = rule_based_model_from_rxncon(rxncon_system)
print(
'Constructed rule-based model: [{} molecule types], [{} rules], [{} observables]'
.format(len(rbm.mol_defs), len(rbm.rules), len(rbm.observables)))
model_str = bngl_from_rule_based_model(rbm)
print('Writing BNGL model file [{}] ...'.format(bngl_model_filename))
with open(bngl_model_filename, mode='w') as f:
f.write(model_str)
def test_kplus_overlaps_with_reaction() -> None:
rxncon_system = Quick("""A_p+_B_[(s)]; ! <Aphos> ; k+ A_[(r1)]-{p} ; k+ A_[(r2)]-{p}
<Aphos>; OR A_[(r1)]-{p}
<Aphos>; OR A_[(r2)]-{p}
C_p+_A_[(r1)]
D_p+_A_[(r2)]""").rxncon_system
rbm = rule_based_model_from_rxncon(rxncon_system)
for rule in rbm.rules:
print(rule)
def post(self, request, system_id=None):
self.system_id = system_id
self.request = request
self.form = RuleForm(self.request.POST or None)
if self.form.is_valid():
media_url = settings.MEDIA_URL
media_root = settings.MEDIA_ROOT
loaded = File.objects.filter(loaded=True)
if not loaded:
system_type = "Quick"
system = Quick.objects.filter(id=system_id)[0]
project_name = system.name
book = RxnconQuick(system.quick_input)
else:
system_type = "File"
system = File.objects.filter(id=system_id)[0]
project_name = system.project_name
book = ExcelBook(system.get_absolute_path())
bngl_model_filename = system.slug + "_model.bngl"
model_path = os.path.join(media_root, system.slug, "rule_based", bngl_model_filename)
if not check_filepath(request, model_path, system, media_root):
if system_type == "Quick":
return quick_detail(request, system_id)
else:
return file_detail(request, system_id)
# pickled_rxncon_system = Rxncon_system.objects.get(project_id=system_id, project_type=system_type)
# rxncon_system = pickle.loads(pickled_rxncon_system.pickled_system)
rxncon_system = book.rxncon_system
rbm = rule_based_model_from_rxncon(rxncon_system)
model_str = bngl_from_rule_based_model(rbm)
if not os.path.exists(os.path.join(media_root, system.slug, "rule_based")):
os.mkdir(os.path.join(media_root, system.slug, "rule_based"))
with open(model_path, mode='w') as f:
f.write(model_str)
r = Rule_based_from_rxnconsys(project_name=project_name, model_path=model_path,
comment=request.POST.get('comment'))
r.save()
messages.info(request, "BoolNet files for project '" + r.project_name + "' successfully created.")
if system_type == "Quick":
Quick.objects.filter(id=system_id).update(rule_based_model=r)
return quick_detail(request, system_id)
else:
File.objects.filter(id=system_id).update(rule_based_model=r)
return file_detail(request, system_id)
def test_simple_system() -> None:
rbm = rule_based_model_from_rxncon(Quick("""A_[b]_ppi+_B_[a]; ! A_[(r)]-{p}
A_[b]_ppi-_B_[a]
C_p+_A_[(r)]
D_p-_A_[(r)]""").rxncon_system)
expected_bngl = '''begin model
begin parameters
NumA 100
NumB 100
NumC 100
NumD 100
k 1.0
end parameters
begin molecule types
A(bD,rR~0~p)
B(aD)
C()
D()
end molecule types
begin seed species
A(bD,rR~0) NumA
B(aD) NumB
C() NumC
D() NumD
end seed species
begin observables
end observables
begin reaction rules
# A_[b]_ppi+_B_[a]
A(bD,rR~p) + B(aD) -> A(bD!1,rR~p).B(aD!1) k
# A_[b]_ppi-_B_[a]
A(bD!1).B(aD!1) -> A(bD) + B(aD) k
# C_p+_A_[(r)]
A(rR~0) + C() -> A(rR~p) + C() k
# D_p-_A_[(r)]
A(rR~p) + D() -> A(rR~0) + D() k
end reaction rules
end model
simulate_nf({t_end=>100,n_steps=>10});
'''
assert bngl_from_rule_based_model(rbm) == expected_bngl
def test_mutually_exclusive_bindings() -> None:
rbm = rule_based_model_from_rxncon(Quick('''C_[A]_ppi+_A_[x]
D_[A]_ppi+_A_[x]
B_p+_A; x C_[A]--A_[x]''').rxncon_system)
expected_rules = [
'A(xD) + C(AD) -> A(xD!1).C(AD!1) k',
'A(xD) + D(AD) -> A(xD!1).D(AD!1) k',
'A(BR~0,xD) + B() -> A(BR~p,xD) + B() k',
'A(BR~0,xD!1).D(AD!1) + B() -> A(BR~p,xD!1).D(AD!1) + B() k'
]
assert len(rbm.rules) == len(expected_rules)
for actual_rule in rbm.rules:
assert any(rule_from_str(rule).is_equivalent_to(actual_rule) for rule in expected_rules)
def test_self_regulation() -> None:
rxn_system = Quick("""Rlm1_[MADS]_bind+_Rlm1Gene
PolII_trsc_Rlm1Gene
Ribo_trsl_Rlm1mRNA""").rxncon_system
rbm = rule_based_model_from_rxncon(rxn_system)
expected_rules = [
'Rlm1(MADSD) + Rlm1Gene(Rlm1D) -> Rlm1(MADSD!1).Rlm1Gene(Rlm1D!1) k',
'PolII() + Rlm1Gene() -> PolII() + Rlm1Gene() + Rlm1mRNA() k',
'Ribo() + Rlm1mRNA() -> Ribo() + Rlm1(MADSD) + Rlm1mRNA() k'
]
assert len(rbm.rules) == len(expected_rules)
for actual_rule in rbm.rules:
assert any(rule_from_str(rule).is_equivalent_to(actual_rule) for rule in expected_rules)
def test_kplus_kminus() -> None:
rbm = rule_based_model_from_rxncon(Quick("""A_[b]_ppi+_B_[a]; k+ A_[(r1)]-{p}
A_[b]_ppi+_B_[a]; k- A_[(r2)]-{p}
C_p+_A_[(r1)]
D_p+_A_[(r2)]""").rxncon_system)
expected_rules = [
'A(r1R~p,r2R~p,bD) + B(aD) -> A(r1R~p,r2R~p,bD!1).B(aD!1) k',
'A(r1R~p,r2R~0,bD) + B(aD) -> A(r1R~p,r2R~0,bD!1).B(aD!1) k',
'A(r1R~0,r2R~p,bD) + B(aD) -> A(r1R~0,r2R~p,bD!1).B(aD!1) k',
'A(r1R~0,r2R~0,bD) + B(aD) -> A(r1R~0,r2R~0,bD!1).B(aD!1) k',
'A(r1R~0) + C() -> A(r1R~p) + C() k',
'A(r2R~0) + D() -> A(r2R~p) + D() k'
]
assert len(rbm.rules) == len(expected_rules)
for actual_rule in rbm.rules:
assert any(rule_from_str(rule).is_equivalent_to(actual_rule) for rule in expected_rules)
def test_trslprocat() -> None:
rxn_system = Quick("""Ribo_trslprocat_Ssy5mRNA
A_p+_Ssy5CAT
B_deg_Ssy5PRO""").rxncon_system
rbm = rule_based_model_from_rxncon(rxn_system)
expected_rules = [
'Ribo() + Ssy5mRNA() -> Ribo() + Ssy5CAT(AR~0,CATPROD!1).Ssy5PRO(PROCATD!1) + Ssy5mRNA() k',
'A() + Ssy5CAT(AR~0) -> A() + Ssy5CAT(AR~p) k',
'B() + Ssy5PRO() -> B() k'
]
assert len(rbm.rules) == len(expected_rules)
for actual_rule in rbm.rules:
assert any(
rule_from_str(rule).is_equivalent_to(actual_rule)
for rule in expected_rules)
def test_simple_system() -> None:
rbm = rule_based_model_from_rxncon(
Quick("""A_[b]_ppi+_B_[a]; ! A_[(r)]-{p}
A_[b]_ppi-_B_[a]
C_p+_A_[(r)]; k+ A_[b]--B_[a]
D_p-_A_[(r)]""").rxncon_system)
expected_bngl = '''begin model
begin parameters
NumA 1000
NumB 1000
NumC 1000
NumD 1000
k_1 1.0 # A_[b]_ppi+_B_[a]
k_2 1.0 # A_[b]_ppi-_B_[a]
k_3_1 1.0 # C_p+_A_[(r)]
k_3_2 1.0 # C_p+_A_[(r)]
k_4 1.0 # D_p-_A_[(r)]
end parameters
begin molecule types
A(bD,rR~0~p)
B(aD)
C()
D()
end molecule types
begin seed species
A(bD,rR~0) NumA
B(aD) NumB
C() NumC
D() NumD
end seed species
begin observables
end observables
begin reaction rules
# Rule 1. rxn: A_[b]_ppi+_B_[a], quant_cont: UniversalSet
A(bD,rR~p) + B(aD) -> A(bD!1,rR~p).B(aD!1) k_1
# Rule 2. rxn: A_[b]_ppi-_B_[a], quant_cont: UniversalSet
A(bD!1).B(aD!1) -> A(bD) + B(aD) k_2
# Rule 3. rxn: C_p+_A_[(r)], quant_cont: A@1_[b]--B@2_[a]
A(bD!1,rR~0).B(aD!1) + C() -> A(bD!1,rR~p).B(aD!1) + C() k_3_1
# Rule 4. rxn: C_p+_A_[(r)], quant_cont: !(A@1_[b]--B@2_[a])
A(bD,rR~0) + C() -> A(bD,rR~p) + C() k_3_2
# Rule 5. rxn: D_p-_A_[(r)], quant_cont: UniversalSet
A(rR~p) + D() -> A(rR~0) + D() k_4
end reaction rules
end model
simulate_nf({t_end=>100,n_steps=>10});
'''
assert bngl_from_rule_based_model(rbm) == expected_bngl
