def collect_processes_metabolites_compartments(
reactions=None):
collection = {}
for reaction in reactions.values():
processes = reaction['processes']
for process in processes:
if process not in collection:
collection[process] = {}
metabolites = collect_reaction_participants_value(
key='metabolite',
criteria={},
participants=reaction['participants'])
for metabolite in metabolites:
if metabolite not in collection[process]:
collection[process][metabolite] = []
compartments = collect_reaction_participants_value(
key='compartment',
criteria={'metabolites': [metabolite]},
participants=reaction['participants'])
for compartment in compartments:
if compartment not in collection[process][metabolite]:
collection[process][metabolite].append(compartment)
return collection
def collect_reaction_transports(
reaction):
metabolites_reactant = collect_reaction_participants_value(
key='metabolite',
criteria={'roles': ['reactant']},
participants=reaction['participants'])
metabolites_product = collect_reaction_participants_value(
key='metabolite',
criteria={'roles': ['product']},
participants=reaction['participants'])
# Collect metabolites that participate as both reactants and products
metabolites = filter_common_elements(
list_one=metabolites_product,
list_two=metabolites_reactant)
transports = []
for metabolite in metabolites:
# Determine metabolite's compartments as reactant and product
compartments_reactant = collect_reaction_participants_value(
key='compartment',
criteria={
'metabolites': [metabolite],
'roles': ['reactant']},
participants=reaction['participants'])
compartments_product = collect_reaction_participants_value(
key='compartment',
criteria={
'metabolites': [metabolite],
'roles': ['product']},
participants=reaction['participants'])
# Determine whether there is a difference between the metabolite's
# compartments as reactant and product
transport = not compare_lists_by_mutual_inclusion(
list_one=compartments_reactant,
list_two=compartments_product)
if transport:
compartments = compartments_reactant + compartments_product
compartments_unique = collect_unique_elements(
elements_original=compartments)
record = {
'metabolite': metabolite,
'compartments': compartments_unique}
transports.append(record)
return transports
def determine_reaction_conversion(
reaction):
reactant_metabolites = collect_reaction_participants_value(
key='metabolite',
criteria={'roles': ['reactant']},
participants=reaction['participants'])
product_metabolites = collect_reaction_participants_value(
key='metabolite',
criteria={'roles': ['product']},
participants=reaction['participants'])
return not compare_lists_by_mutual_inclusion(
list_one=reactant_metabolites,
list_two=product_metabolites)
def collect_reactions_replicates(
reactions):
reactions_replicates = []
for reaction in reactions.values():
identifier = reaction['identifier']
# Collect identifiers of metabolites that participate as reactants and
# products in the reaction
reactants = collect_reaction_participants_value(
key='metabolite',
criteria={'roles': ['reactant']},
participants=reaction['participants'])
products = collect_reaction_participants_value(
key='metabolite',
criteria={'roles': ['product']},
participants=reaction['participants'])
# Determine whether collection includes a record for an identical
# combination of reactants and products
index = find_index_reactions_replicates_reactants_products(
reactants=reactants,
products=products,
reactions_replicates=reactions_replicates)
if index == -1:
# Record does not exist
# Create novel record
record = {
'reactions': [reaction['identifier']],
'reactants': reactants,
'products': products}
reactions_replicates.append(record)
else:
# Record exists
# Include reaction in record
reactions_replicates[index]['reactions'].append(identifier)
return reactions_replicates
def convert_reactions_export_text(reactions, metabolites, compartments,
processes):
records = []
for reaction in reactions.values():
# Get participants
# Write a function to compose identifier (name) human readable...
# Compartments
compartments_identifiers = collect_value_from_records(
key='compartment', records=reaction['participants'])
compartments_identifiers_unique = collect_unique_elements(
elements_original=compartments_identifiers)
compartments_names = collect_values_from_records_in_reference(
key='name',
identifiers=compartments_identifiers_unique,
reference=compartments)
# Processes
processes_names = collect_values_from_records_in_reference(
key='name', identifiers=reaction['processes'], reference=processes)
# Metabolites
reactants_identifiers = collect_reaction_participants_value(
key='metabolite',
criteria={'roles': ['reactant']},
participants=reaction['participants'])
reactants_names = collect_values_from_records_in_reference(
key='name',
identifiers=reactants_identifiers,
reference=metabolites)
products_identifiers = collect_reaction_participants_value(
key='metabolite',
criteria={'roles': ['product']},
participants=reaction['participants'])
products_names = collect_values_from_records_in_reference(
key='name',
identifiers=products_identifiers,
reference=metabolites)
# Compile information
record = {
'identifier': reaction['identifier'],
'name': reaction['name'],
'reactants': '; '.join(reactants_names),
'products': '; '.join(products_names),
'compartments': '; '.join(compartments_names),
'processes': ';'.join(processes_names),
'reversibility': reaction['reversibility'],
'reference_metanetx':
('; '.join(reaction['references']['metanetx'])),
'reference_recon': ('; '.join(reaction['references']['recon'])),
'reference_gene': '; '.join(reaction['references']['gene']),
'reference_enzyme': '; '.join(reaction['references']['enzyme']),
'reference_kegg': '; '.join(reaction['references']['kegg']),
'reference_reactome':
('; '.join(reaction['references']['reactome'])),
'reference_metacyc': '; '.join(reaction['references']['metacyc']),
'reference_bigg': '; '.join(reaction['references']['bigg'])
}
records.append(record)
return records