def change_model_metabolites(curation_metabolites=None, content=None):
"""
Changes metabolites' identifiers
This function changes metabolites' identifiers according to information
about translation.
arguments:
curation_metabolites (list<dict<str>>): changes to information about
metabolites
content (object): content from file in Systems Biology Markup Language
(XML)
raises:
returns:
(object): content with changes
"""
# Copy and interpret content.
reference = metabocurator_collection.copy_interpret_content_recon2m2(
content=content)
# Change content for each combination of original and novel identifiers.
for row in curation_metabolites:
# Construct targets to recognize original and novel identifiers.
# Use trailing underscore to match complete identifiers.
original_elements = [row["identifier_original"], "_"]
original_target = "".join(original_elements)
novel_elements = [row["identifier_novel"], "_"]
novel_target = "".join(novel_elements)
# Change identifiers of metabolites.
for metabolite in reference["metabolites"].findall(
"version:species", reference["space"]):
# Determine whether to change metabolite's identifier.
if original_target in metabolite.attrib["id"]:
metabolite.attrib["id"] = metabolite.attrib["id"].replace(
original_target, novel_target)
# Change identifiers of reactions' metabolites.
for reaction in reference["reactions"].findall("version:reaction",
reference["space"]):
# Search reaction's metabolites.
for metabolite in reaction.iter(
"{http://www.sbml.org/sbml/level2/version4}speciesReference"
):
# Determine whether to change metabolite's identifier.
if original_target in metabolite.attrib["species"]:
metabolite.attrib["species"] = (
metabolite.attrib["species"].replace(
original_target, novel_target))
# Return content with changes.
return reference["content"]
def remove_model_metabolite_prefix(content=None):
"""
Removes unnecessary prefixes from identifiers for model's entities
This function removes unnecessary prefixes from identifiers for
metabolites.
arguments:
content (object): content from file in Systems Biology Markup Language
(XML)
raises:
returns:
(object): content with changes
"""
# Copy and interpret content.
reference = metabocurator_collection.copy_interpret_content_recon2m2(
content=content)
# Remove prefixes from identifiers for metabolites.
for metabolite in reference["metabolites"].findall("version:species",
reference["space"]):
# Remove prefix from metabolite's identifier.
novel_identifier = re.sub(r"^M_", "", metabolite.attrib["id"])
metabolite.attrib["id"] = novel_identifier
# Search metabolite's annotation.
for description in metabolite.iter(
"{http://www.w3.org/1999/02/22-rdf-syntax-ns#}description"):
# Remove prefix from metabolite's identifier.
novel_identifier = re.sub(
r"^#M_", "#", description.
attrib["{http://www.w3.org/1999/02/22-rdf-syntax-ns#}about"])
description.attrib[
"{http://www.w3.org/1999/02/22-rdf-syntax-ns#}about"] = novel_identifier
# Remove prefixes from identifiers for reactions' metabolites.
for reaction in reference["reactions"].findall("version:reaction",
reference["space"]):
# Search reaction's metabolites.
for metabolite in reaction.iter(
"{http://www.sbml.org/sbml/level2/version4}speciesReference"):
# Remove prefix from metabolite's identifier.
novel_identifier = re.sub(r"^M_", "", metabolite.attrib["species"])
metabolite.attrib["species"] = novel_identifier
# Return content with changes.
return reference["content"]
def change_model_boundary(content=None):
"""
Changes annotations for a model's boundary
This function changes annotations of a model's boundary in compartments,
metabolites, and reactions.
arguments:
content (object): content from file in Systems Biology Markup Language
(XML)
raises:
returns:
(object): content with changes
"""
# Copy and interpret content.
reference = metabocurator_collection.copy_interpret_content_recon2m2(
content=content)
# Correct designation of model's boundary in metabolites.
for metabolite in reference["metabolites"].findall("version:species",
reference["space"]):
# Determine whether metabolite's compartment is model's boundary.
if "boundary" in metabolite.attrib["id"]:
novel_identifier = re.sub(r"_[eciglmnrx]_boundary", "_b",
metabolite.attrib["id"])
metabolite.attrib["id"] = novel_identifier
novel_compartment = "b"
metabolite.attrib["compartment"] = novel_compartment
# Correct designation of model's boundary in reactions.
for reaction in reference["reactions"].findall("version:reaction",
reference["space"]):
# Search reaction's metabolites.
for metabolite in reaction.iter(
"{http://www.sbml.org/sbml/level2/version4}speciesReference"):
# Determine whether metabolite's compartment is model's boundary.
if "boundary" in metabolite.attrib["species"]:
novel_identifier = re.sub(r"_[eciglmnrx]_boundary", "_b",
metabolite.attrib["species"])
metabolite.attrib["species"] = novel_identifier
# Return content with changes.
return reference["content"]
def count_model_sets_entities(content=None):
"""
Counts compartments, reactions, and metabolites in model.
arguments:
content (object): content from file in Systems Biology Markup Language
(XML)
raises:
returns:
(dict<int>): summary
"""
# Copy and interpret content.
reference = metabocurator_collection.copy_interpret_content_recon2m2(
content=content)
# Count compartments.
compartments = 0
for compartment in reference["compartments"].findall(
"version:compartment", reference["space"]):
compartments = compartments + 1
# Count reactions.
reactions = 0
for reaction in reference["reactions"].findall("version:reaction",
reference["space"]):
reactions = reactions + 1
# Count metabolites.
metabolites = 0
for metabolite in reference["metabolites"].findall("version:species",
reference["space"]):
metabolites = metabolites + 1
# Compile and return inforation.
return {
"compartments": compartments,
"reactions": reactions,
"metabolites": metabolites
}