pypath.core.interaction.Interaction§

class pypath.core.interaction.Interaction(a, b, id_type_a='uniprot', id_type_b='uniprot', entity_type_a='protein', entity_type_b='protein', taxon_a=9606, taxon_b=9606, attrs=None)[source]§

Bases: AttributeHandler

Represents a unique pair of molecular entities interacting with each other. One Interaction object might represent multiple interactions i.e. with different direction or effect or type (e.g. transcriptional regulation and post-translational regulation), each supported by different evidences.

Parameters:

a,b (str,pypath.entity.Entity) – The two interacting partners. If an pypath.entity.Entity objects provided the other attributes (entity_type, id_type, taxon) will be ignored.
id_type_a,id_type_b (str) – The identifier types for partner a and b e.g. 'uniprot'.
entity_type_a,entity_type_b (str) – The types of the molecular entities a and b e.g. 'protein'.
taxon_a,taxon_b (int) – The NCBI Taxonomy Identifiers of partner a and b e.g. 9606 for human.

Details:

The arguments a and b will be assigned to the attribute a and b in an alphabetical order, hence it’s possible that argument a becomes attribute b.

__init__(a, b, id_type_a='uniprot', id_type_b='uniprot', entity_type_a='protein', entity_type_b='protein', taxon_a=9606, taxon_b=9606, attrs=None)[source]§

Methods

`__init__`(a, b[, id_type_a, id_type_b, ...])
`add_evidence`(evidence[, direction, effect, ...])	Adds directionality information with the corresponding data source named.
`add_sign`(direction, sign[, resource, ...])	Sets sign and source information on a given direction of the edge.
`asdict`(direction)	Dictionary representation of the evidences.
`complex_identifiers_by_data_model`([effect, ...])	Retrieves the entities involved in interactions matching the criteria.
`complex_identifiers_by_interaction_type`([...])	Retrieves the entities involved in interactions matching the criteria.
`complex_identifiers_by_interaction_type_and_data_model`([...])	Retrieves the entities involved in interactions matching the criteria.
`complex_identifiers_by_interaction_type_and_data_model_and_resource`([...])	Retrieves the entities involved in interactions matching the criteria.
`complex_identifiers_by_reference`([effect, ...])	Retrieves the entities involved in interactions matching the criteria.
`complex_identifiers_by_resource`([effect, ...])	Retrieves the entities involved in interactions matching the criteria.
`complex_labels_by_data_model`([effect, ...])	Retrieves the entities involved in interactions matching the criteria.
`complex_labels_by_interaction_type`([effect, ...])	Retrieves the entities involved in interactions matching the criteria.
`complex_labels_by_interaction_type_and_data_model`([...])	Retrieves the entities involved in interactions matching the criteria.
`complex_labels_by_interaction_type_and_data_model_and_resource`([...])	Retrieves the entities involved in interactions matching the criteria.
`complex_labels_by_reference`([effect, ...])	Retrieves the entities involved in interactions matching the criteria.
`complex_labels_by_resource`([effect, ...])	Retrieves the entities involved in interactions matching the criteria.
`complexes_by_data_model`([effect, resources, ...])	Retrieves the entities involved in interactions matching the criteria.
`complexes_by_interaction_type`([effect, ...])	Retrieves the entities involved in interactions matching the criteria.
`complexes_by_interaction_type_and_data_model`([...])	Retrieves the entities involved in interactions matching the criteria.
`complexes_by_interaction_type_and_data_model_and_resource`([...])	Retrieves the entities involved in interactions matching the criteria.
`complexes_by_reference`([effect, resources, ...])	Retrieves the entities involved in interactions matching the criteria.
`complexes_by_resource`([effect, resources, ...])	Retrieves the entities involved in interactions matching the criteria.
`consensus`([only_interaction_type, ...])	Infers the consensus edge(s) according to the number of supporting sources.
`consensus_edges`([only_interaction_type, ...])	Infers the consensus edge(s) according to the number of supporting sources.
`count_complex_identifiers`([effect, ...])	Retrieves the entities involved in interactions matching the criteria.
`count_complex_labels`([effect, resources, ...])	Retrieves the entities involved in interactions matching the criteria.
`count_complexes`([effect, resources, ...])	Retrieves the entities involved in interactions matching the criteria.
`count_curation_effort`([effect, resources, ...])
`count_entities`([effect, resources, ...])	Retrieves the entities involved in interactions matching the criteria.
`count_identifiers`([effect, resources, ...])	Retrieves the entities involved in interactions matching the criteria.
`count_interactions`([effect, resources, ...])	Returns one or two tuples of the interacting partners: one if only one direction, two if both directions match the query criteria.
`count_interactions_0`([effect, resources, ...])	Returns unique interacting pairs without being aware of the direction.
`count_interactions_directed`([effect, ...])	Args
`count_interactions_mutual`(**kwargs)	Note: undirected interactions does not count as mutual but only interactions with explicit direction information for both directions.
`count_interactions_negative`([effect, ...])	Args
`count_interactions_non_directed`(**kwargs)	Returns True if any resource annotates this interaction without and no resource with direction.
`count_interactions_positive`([effect, ...])	Args
`count_interactions_signed`([effect, ...])	Args
`count_interactions_undirected`(**kwargs)	Returns True if any resource annotates this interaction without direction.
`count_labels`([effect, resources, ...])	Retrieves the entities involved in interactions matching the criteria.
`count_lncrna_identifiers`([effect, ...])	Retrieves the entities involved in interactions matching the criteria.
`count_lncrna_labels`([effect, resources, ...])	Retrieves the entities involved in interactions matching the criteria.
`count_lncrnas`([effect, resources, ...])	Retrieves the entities involved in interactions matching the criteria.
`count_mirna_identifiers`([effect, resources, ...])	Retrieves the entities involved in interactions matching the criteria.
`count_mirna_labels`([effect, resources, ...])	Retrieves the entities involved in interactions matching the criteria.
`count_mirnas`([effect, resources, ...])	Retrieves the entities involved in interactions matching the criteria.
`count_protein_identifiers`([effect, ...])	Retrieves the entities involved in interactions matching the criteria.
`count_protein_labels`([effect, resources, ...])	Retrieves the entities involved in interactions matching the criteria.
`count_proteins`([effect, resources, ...])	Retrieves the entities involved in interactions matching the criteria.
`count_small_molecule_identifiers`([effect, ...])	Retrieves the entities involved in interactions matching the criteria.
`count_small_molecule_labels`([effect, ...])	Retrieves the entities involved in interactions matching the criteria.
`count_small_molecules`([effect, resources, ...])	Retrieves the entities involved in interactions matching the criteria.
`curation_effort_by_data_model`([effect, ...])
`curation_effort_by_interaction_type`([...])
`curation_effort_by_interaction_type_and_data_model`([...])
`curation_effort_by_interaction_type_and_data_model_and_resource`([...])
`curation_effort_by_reference`([effect, ...])
`curation_effort_by_resource`([effect, ...])
`direction_key`(direction)	The direction keys are tuples of Entity objects; this method creates these tuples from a tuple of strings.
`direction_key_identifiers`(direction)
`dorothea_level`(direction)	DoRothEA confidence level for one direction as a single letter.
`dorothea_levels`([direction])	Retrieves the DoRothEA confidence levels.
`entities_by_data_model`([effect, resources, ...])	Retrieves the entities involved in interactions matching the criteria.
`entities_by_interaction_type`([effect, ...])	Retrieves the entities involved in interactions matching the criteria.
`entities_by_interaction_type_and_data_model`([...])	Retrieves the entities involved in interactions matching the criteria.
`entities_by_interaction_type_and_data_model_and_resource`([...])	Retrieves the entities involved in interactions matching the criteria.
`entities_by_reference`([effect, resources, ...])	Retrieves the entities involved in interactions matching the criteria.
`entities_by_resource`([effect, resources, ...])	Retrieves the entities involved in interactions matching the criteria.
`evaluate_evidences`(this_direction[, ...])	Selects the evidence collections matching the direction and effect criteria and then evaluates if any of the evidences in these collections match the evidence criteria.
`evidences_by_data_model`([effect, resources, ...])
`evidences_by_interaction_type`([effect, ...])
`evidences_by_interaction_type_and_data_model`([...])
`evidences_by_interaction_type_and_data_model_and_resource`([...])
`evidences_by_reference`([effect, resources, ...])
`evidences_by_resource`([effect, resources, ...])
`generate_df_records`([by_source, with_references])	Yields interaction records.
`get_attr`(resource, key[, direction])	Extracts the values of one specific attribute.
`get_complex_identifiers`([entity_type, ...])	Retrieves the entities involved in interactions matching the criteria.
`get_complex_labels`([entity_type, direction, ...])	Retrieves the entities involved in interactions matching the criteria.
`get_complexes`([entity_type, direction, ...])	Retrieves the entities involved in interactions matching the criteria.
`get_curation_effort`(**kwargs)
`get_degrees`(mode[, direction, effect, ...])	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`get_direction`(direction[, resources, ...])	Returns the state (or resources if specified) of the given direction.
`get_directions`(src, tgt[, resources, ...])	Returns all directions with boolean values or list of sources.
`get_entities`([entity_type, direction, ...])	Retrieves the entities involved in interactions matching the criteria.
`get_evidences`([direction, effect, ...])
`get_identifiers`([entity_type, direction, ...])	Retrieves the entities involved in interactions matching the criteria.
`get_interactions`([direction, effect, ...])	Returns one or two tuples of the interacting partners: one if only one direction, two if both directions match the query criteria.
`get_interactions_0`(**kwargs)	Returns unique interacting pairs without being aware of the direction.
`get_interactions_directed`(**kwargs)	Args
`get_interactions_mutual`(**kwargs)	Note: undirected interactions does not count as mutual but only interactions with explicit direction information for both directions.
`get_interactions_negative`(**kwargs)	Args
`get_interactions_non_directed`(**kwargs)	Only the undirected interactions will be considered, if any resource annotates this interaction as undirected both directions will be returned, but only if no resource provide direction.
`get_interactions_non_directed_0`(**kwargs)	Only the undirected interactions will be considered, if any resource annotates this interaction as undirected and none as directed, the interacting pair as a sorted tuple will be returned inside a one element tuple.
`get_interactions_positive`(**kwargs)	Args
`get_interactions_signed`(**kwargs)	Args
`get_interactions_undirected`(**kwargs)	Only the undirected interactions will be considered, if any resource annotates this interaction as undirected both directions will be returned, no matter if certain resources provide direction.
`get_interactions_undirected_0`(**kwargs)	Only the undirected interactions will be considered, if any resource annotates this interaction as undirected the interacting pair as a sorted tuple will be returned inside a one element tuple.
`get_labels`([entity_type, direction, effect, ...])	Retrieves the entities involved in interactions matching the criteria.
`get_lncrna_identifiers`([entity_type, ...])	Retrieves the entities involved in interactions matching the criteria.
`get_lncrna_labels`([entity_type, direction, ...])	Retrieves the entities involved in interactions matching the criteria.
`get_lncrnas`([entity_type, direction, ...])	Retrieves the entities involved in interactions matching the criteria.
`get_mirna_identifiers`([entity_type, ...])	Retrieves the entities involved in interactions matching the criteria.
`get_mirna_labels`([entity_type, direction, ...])	Retrieves the entities involved in interactions matching the criteria.
`get_mirnas`([entity_type, direction, effect, ...])	Retrieves the entities involved in interactions matching the criteria.
`get_protein_identifiers`([entity_type, ...])	Retrieves the entities involved in interactions matching the criteria.
`get_protein_labels`([entity_type, direction, ...])	Retrieves the entities involved in interactions matching the criteria.
`get_proteins`([entity_type, direction, ...])	Retrieves the entities involved in interactions matching the criteria.
`get_sign`(direction[, sign, evidences, ...])	Retrieves the sign information of the edge in the given diretion.
`get_small_molecule_identifiers`([...])	Retrieves the entities involved in interactions matching the criteria.
`get_small_molecule_labels`([entity_type, ...])	Retrieves the entities involved in interactions matching the criteria.
`get_small_molecules`([entity_type, ...])	Retrieves the entities involved in interactions matching the criteria.
`has_data_model`(data_model)
`has_dataset`(dataset[, direction, effect])
`has_sign`([direction, resources])	Checks whether the edge (or for a specific direction) has any signed information (about positive/negative interactions).
`id_to_entity`(identifier)
`identifiers_by_data_model`([effect, ...])	Retrieves the entities involved in interactions matching the criteria.
`identifiers_by_interaction_type`([effect, ...])	Retrieves the entities involved in interactions matching the criteria.
`identifiers_by_interaction_type_and_data_model`([...])	Retrieves the entities involved in interactions matching the criteria.
`identifiers_by_interaction_type_and_data_model_and_resource`([...])	Retrieves the entities involved in interactions matching the criteria.
`identifiers_by_reference`([effect, ...])	Retrieves the entities involved in interactions matching the criteria.
`identifiers_by_resource`([effect, resources, ...])	Retrieves the entities involved in interactions matching the criteria.
`interactions_0_by_data_model`([effect, ...])	Returns unique interacting pairs without being aware of the direction.
`interactions_0_by_interaction_type`([effect, ...])	Returns unique interacting pairs without being aware of the direction.
`interactions_0_by_interaction_type_and_data_model`([...])	Returns unique interacting pairs without being aware of the direction.
`interactions_0_by_interaction_type_and_data_model_and_resource`([...])	Returns unique interacting pairs without being aware of the direction.
`interactions_0_by_reference`([effect, ...])	Returns unique interacting pairs without being aware of the direction.
`interactions_0_by_resource`([effect, ...])	Returns unique interacting pairs without being aware of the direction.
`interactions_by_data_model`([effect, ...])	Returns one or two tuples of the interacting partners: one if only one direction, two if both directions match the query criteria.
`interactions_by_interaction_type`([effect, ...])	Returns one or two tuples of the interacting partners: one if only one direction, two if both directions match the query criteria.
`interactions_by_interaction_type_and_data_model`([...])	Returns one or two tuples of the interacting partners: one if only one direction, two if both directions match the query criteria.
`interactions_by_interaction_type_and_data_model_and_resource`([...])	Returns one or two tuples of the interacting partners: one if only one direction, two if both directions match the query criteria.
`interactions_by_reference`([effect, ...])	Returns one or two tuples of the interacting partners: one if only one direction, two if both directions match the query criteria.
`interactions_by_resource`([effect, ...])	Returns one or two tuples of the interacting partners: one if only one direction, two if both directions match the query criteria.
`interactions_directed_by_data_model`([...])	Args
`interactions_directed_by_interaction_type`([...])	Args
`interactions_directed_by_interaction_type_and_data_model`([...])	Args
`interactions_directed_by_interaction_type_and_data_model_and_resource`([...])	Args
`interactions_directed_by_reference`([effect, ...])	Args
`interactions_directed_by_resource`([effect, ...])	Args
`interactions_mutual_by_data_model`([effect, ...])	Note: undirected interactions does not count as mutual but only interactions with explicit direction information for both directions.
`interactions_mutual_by_interaction_type`([...])	Note: undirected interactions does not count as mutual but only interactions with explicit direction information for both directions.
`interactions_mutual_by_interaction_type_and_data_model`([...])	Note: undirected interactions does not count as mutual but only interactions with explicit direction information for both directions.
`interactions_mutual_by_interaction_type_and_data_model_and_resource`([...])	Note: undirected interactions does not count as mutual but only interactions with explicit direction information for both directions.
`interactions_mutual_by_reference`([effect, ...])	Note: undirected interactions does not count as mutual but only interactions with explicit direction information for both directions.
`interactions_mutual_by_resource`([effect, ...])	Note: undirected interactions does not count as mutual but only interactions with explicit direction information for both directions.
`interactions_negative_by_data_model`([...])	Args
`interactions_negative_by_interaction_type`([...])	Args
`interactions_negative_by_interaction_type_and_data_model`([...])	Args
`interactions_negative_by_interaction_type_and_data_model_and_resource`([...])	Args
`interactions_negative_by_reference`([effect, ...])	Args
`interactions_negative_by_resource`([effect, ...])	Args
`interactions_non_directed_0_by_data_model`([...])	Only the undirected interactions will be considered, if any resource annotates this interaction as undirected and none as directed, the interacting pair as a sorted tuple will be returned inside a one element tuple.
`interactions_non_directed_0_by_interaction_type`([...])	Only the undirected interactions will be considered, if any resource annotates this interaction as undirected and none as directed, the interacting pair as a sorted tuple will be returned inside a one element tuple.
`interactions_non_directed_0_by_interaction_type_and_data_model`([...])	Only the undirected interactions will be considered, if any resource annotates this interaction as undirected and none as directed, the interacting pair as a sorted tuple will be returned inside a one element tuple.
`interactions_non_directed_0_by_interaction_type_and_data_model_and_resource`([...])	Only the undirected interactions will be considered, if any resource annotates this interaction as undirected and none as directed, the interacting pair as a sorted tuple will be returned inside a one element tuple.
`interactions_non_directed_0_by_reference`([...])	Only the undirected interactions will be considered, if any resource annotates this interaction as undirected and none as directed, the interacting pair as a sorted tuple will be returned inside a one element tuple.
`interactions_non_directed_0_by_resource`([...])	Only the undirected interactions will be considered, if any resource annotates this interaction as undirected and none as directed, the interacting pair as a sorted tuple will be returned inside a one element tuple.
`interactions_non_directed_by_data_model`([...])	Only the undirected interactions will be considered, if any resource annotates this interaction as undirected both directions will be returned, but only if no resource provide direction.
`interactions_non_directed_by_interaction_type`([...])	Only the undirected interactions will be considered, if any resource annotates this interaction as undirected both directions will be returned, but only if no resource provide direction.
`interactions_non_directed_by_interaction_type_and_data_model`([...])	Only the undirected interactions will be considered, if any resource annotates this interaction as undirected both directions will be returned, but only if no resource provide direction.
`interactions_non_directed_by_interaction_type_and_data_model_and_resource`([...])	Only the undirected interactions will be considered, if any resource annotates this interaction as undirected both directions will be returned, but only if no resource provide direction.
`interactions_non_directed_by_reference`([...])	Only the undirected interactions will be considered, if any resource annotates this interaction as undirected both directions will be returned, but only if no resource provide direction.
`interactions_non_directed_by_resource`([...])	Only the undirected interactions will be considered, if any resource annotates this interaction as undirected both directions will be returned, but only if no resource provide direction.
`interactions_positive_by_data_model`([...])	Args
`interactions_positive_by_interaction_type`([...])	Args
`interactions_positive_by_interaction_type_and_data_model`([...])	Args
`interactions_positive_by_interaction_type_and_data_model_and_resource`([...])	Args
`interactions_positive_by_reference`([effect, ...])	Args
`interactions_positive_by_resource`([effect, ...])	Args
`interactions_signed_by_data_model`([effect, ...])	Args
`interactions_signed_by_interaction_type`([...])	Args
`interactions_signed_by_interaction_type_and_data_model`([...])	Args
`interactions_signed_by_interaction_type_and_data_model_and_resource`([...])	Args
`interactions_signed_by_reference`([effect, ...])	Args
`interactions_signed_by_resource`([effect, ...])	Args
`interactions_undirected_0_by_data_model`([...])	Only the undirected interactions will be considered, if any resource annotates this interaction as undirected the interacting pair as a sorted tuple will be returned inside a one element tuple.
`interactions_undirected_0_by_interaction_type`([...])	Only the undirected interactions will be considered, if any resource annotates this interaction as undirected the interacting pair as a sorted tuple will be returned inside a one element tuple.
`interactions_undirected_0_by_interaction_type_and_data_model`([...])	Only the undirected interactions will be considered, if any resource annotates this interaction as undirected the interacting pair as a sorted tuple will be returned inside a one element tuple.
`interactions_undirected_0_by_interaction_type_and_data_model_and_resource`([...])	Only the undirected interactions will be considered, if any resource annotates this interaction as undirected the interacting pair as a sorted tuple will be returned inside a one element tuple.
`interactions_undirected_0_by_reference`([...])	Only the undirected interactions will be considered, if any resource annotates this interaction as undirected the interacting pair as a sorted tuple will be returned inside a one element tuple.
`interactions_undirected_0_by_resource`([...])	Only the undirected interactions will be considered, if any resource annotates this interaction as undirected the interacting pair as a sorted tuple will be returned inside a one element tuple.
`interactions_undirected_by_data_model`([...])	Only the undirected interactions will be considered, if any resource annotates this interaction as undirected both directions will be returned, no matter if certain resources provide direction.
`interactions_undirected_by_interaction_type`([...])	Only the undirected interactions will be considered, if any resource annotates this interaction as undirected both directions will be returned, no matter if certain resources provide direction.
`interactions_undirected_by_interaction_type_and_data_model`([...])	Only the undirected interactions will be considered, if any resource annotates this interaction as undirected both directions will be returned, no matter if certain resources provide direction.
`interactions_undirected_by_interaction_type_and_data_model_and_resource`([...])	Only the undirected interactions will be considered, if any resource annotates this interaction as undirected both directions will be returned, no matter if certain resources provide direction.
`interactions_undirected_by_reference`([...])	Only the undirected interactions will be considered, if any resource annotates this interaction as undirected both directions will be returned, no matter if certain resources provide direction.
`interactions_undirected_by_resource`([...])	Only the undirected interactions will be considered, if any resource annotates this interaction as undirected both directions will be returned, no matter if certain resources provide direction.
`is_directed`()	Checks if edge has any directionality information.
`is_directed_by_resources`([resources])	Checks if edge has any directionality information from some resource(s).
`is_inhibition`([direction, resources])	Checks if any (or for a specific direction) interaction is inhibition (negative interaction).
`is_loop`()	returns:
`is_mutual`(**kwargs)	Note: undirected interactions does not count as mutual but only interactions with explicit direction information for both directions.
`is_mutual_by_resources`([resources])	Checks if the edge has mutual directions (both A-->B and B-->A) according to some resource(s).
`is_stimulation`([direction, resources])	Checks if any (or for a specific direction) interaction is activation (positive interaction).
`iter_evidences`(this_direction[, direction, ...])	Selects and yields evidence collections matching the direction and effect criteria.
`iter_match_evidences`(this_direction[, ...])	Selects the evidence collections matching the direction and effect criteria and yields collections matching the evidence criteria.
`labels_by_data_model`([effect, resources, ...])	Retrieves the entities involved in interactions matching the criteria.
`labels_by_interaction_type`([effect, ...])	Retrieves the entities involved in interactions matching the criteria.
`labels_by_interaction_type_and_data_model`([...])	Retrieves the entities involved in interactions matching the criteria.
`labels_by_interaction_type_and_data_model_and_resource`([...])	Retrieves the entities involved in interactions matching the criteria.
`labels_by_reference`([effect, resources, ...])	Retrieves the entities involved in interactions matching the criteria.
`labels_by_resource`([effect, resources, ...])	Retrieves the entities involved in interactions matching the criteria.
`lncrna_identifiers_by_data_model`([effect, ...])	Retrieves the entities involved in interactions matching the criteria.
`lncrna_identifiers_by_interaction_type`([...])	Retrieves the entities involved in interactions matching the criteria.
`lncrna_identifiers_by_interaction_type_and_data_model`([...])	Retrieves the entities involved in interactions matching the criteria.
`lncrna_identifiers_by_interaction_type_and_data_model_and_resource`([...])	Retrieves the entities involved in interactions matching the criteria.
`lncrna_identifiers_by_reference`([effect, ...])	Retrieves the entities involved in interactions matching the criteria.
`lncrna_identifiers_by_resource`([effect, ...])	Retrieves the entities involved in interactions matching the criteria.
`lncrna_labels_by_data_model`([effect, ...])	Retrieves the entities involved in interactions matching the criteria.
`lncrna_labels_by_interaction_type`([effect, ...])	Retrieves the entities involved in interactions matching the criteria.
`lncrna_labels_by_interaction_type_and_data_model`([...])	Retrieves the entities involved in interactions matching the criteria.
`lncrna_labels_by_interaction_type_and_data_model_and_resource`([...])	Retrieves the entities involved in interactions matching the criteria.
`lncrna_labels_by_reference`([effect, ...])	Retrieves the entities involved in interactions matching the criteria.
`lncrna_labels_by_resource`([effect, ...])	Retrieves the entities involved in interactions matching the criteria.
`lncrnas_by_data_model`([effect, resources, ...])	Retrieves the entities involved in interactions matching the criteria.
`lncrnas_by_interaction_type`([effect, ...])	Retrieves the entities involved in interactions matching the criteria.
`lncrnas_by_interaction_type_and_data_model`([...])	Retrieves the entities involved in interactions matching the criteria.
`lncrnas_by_interaction_type_and_data_model_and_resource`([...])	Retrieves the entities involved in interactions matching the criteria.
`lncrnas_by_reference`([effect, resources, ...])	Retrieves the entities involved in interactions matching the criteria.
`lncrnas_by_resource`([effect, resources, ...])	Retrieves the entities involved in interactions matching the criteria.
`majority_dir`([only_interaction_type, ...])	Infers which is the major directionality of the edge by number of supporting sources.
`majority_sign`([only_interaction_type, ...])	Infers which is the major sign (activation/inhibition) of the edge by number of supporting sources on both directions.
`merge`(other)	Merges current Interaction with another (if and only if they are the same class and contain the same nodes).
`mirna_identifiers_by_data_model`([effect, ...])	Retrieves the entities involved in interactions matching the criteria.
`mirna_identifiers_by_interaction_type`([...])	Retrieves the entities involved in interactions matching the criteria.
`mirna_identifiers_by_interaction_type_and_data_model`([...])	Retrieves the entities involved in interactions matching the criteria.
`mirna_identifiers_by_interaction_type_and_data_model_and_resource`([...])	Retrieves the entities involved in interactions matching the criteria.
`mirna_identifiers_by_reference`([effect, ...])	Retrieves the entities involved in interactions matching the criteria.
`mirna_identifiers_by_resource`([effect, ...])	Retrieves the entities involved in interactions matching the criteria.
`mirna_labels_by_data_model`([effect, ...])	Retrieves the entities involved in interactions matching the criteria.
`mirna_labels_by_interaction_type`([effect, ...])	Retrieves the entities involved in interactions matching the criteria.
`mirna_labels_by_interaction_type_and_data_model`([...])	Retrieves the entities involved in interactions matching the criteria.
`mirna_labels_by_interaction_type_and_data_model_and_resource`([...])	Retrieves the entities involved in interactions matching the criteria.
`mirna_labels_by_reference`([effect, ...])	Retrieves the entities involved in interactions matching the criteria.
`mirna_labels_by_resource`([effect, ...])	Retrieves the entities involved in interactions matching the criteria.
`mirnas_by_data_model`([effect, resources, ...])	Retrieves the entities involved in interactions matching the criteria.
`mirnas_by_interaction_type`([effect, ...])	Retrieves the entities involved in interactions matching the criteria.
`mirnas_by_interaction_type_and_data_model`([...])	Retrieves the entities involved in interactions matching the criteria.
`mirnas_by_interaction_type_and_data_model_and_resource`([...])	Retrieves the entities involved in interactions matching the criteria.
`mirnas_by_reference`([effect, resources, ...])	Retrieves the entities involved in interactions matching the criteria.
`mirnas_by_resource`([effect, resources, ...])	Retrieves the entities involved in interactions matching the criteria.
`negative_a_b`()	Checks if the `a_b` directionality is a negative interaction.
`negative_b_a`()	Checks if the `b_a` directionality is a negative interaction.
`negative_resources_a_b`(**kwargs)	Retrieves the list of resources for the `a_b` direction and negative sign.
`negative_resources_b_a`(**kwargs)	Retrieves the list of resources for the `b_a` direction and negative sign.
`negative_reverse`()	Checks if the `b_a` directionality is a negative interaction.
`negative_straight`()	Checks if the `a_b` directionality is a negative interaction.
`orthology_translate`(taxon[, exclude])
`orthology_translate_one`(id_a, id_b, taxon)
`positive_a_b`()	Checks if the `a_b` directionality is a positive interaction.
`positive_b_a`()	Checks if the `b_a` directionality is a positive interaction.
`positive_resources_a_b`(**kwargs)	Retrieves the list of resources for the `a_b` direction and positive sign.
`positive_resources_b_a`(**kwargs)	Retrieves the list of resources for the `b_a` direction and positive sign.
`positive_reverse`()	Checks if the `b_a` directionality is a positive interaction.
`positive_straight`()	Checks if the `a_b` directionality is a positive interaction.
`protein_identifiers_by_data_model`([effect, ...])	Retrieves the entities involved in interactions matching the criteria.
`protein_identifiers_by_interaction_type`([...])	Retrieves the entities involved in interactions matching the criteria.
`protein_identifiers_by_interaction_type_and_data_model`([...])	Retrieves the entities involved in interactions matching the criteria.
`protein_identifiers_by_interaction_type_and_data_model_and_resource`([...])	Retrieves the entities involved in interactions matching the criteria.
`protein_identifiers_by_reference`([effect, ...])	Retrieves the entities involved in interactions matching the criteria.
`protein_identifiers_by_resource`([effect, ...])	Retrieves the entities involved in interactions matching the criteria.
`protein_labels_by_data_model`([effect, ...])	Retrieves the entities involved in interactions matching the criteria.
`protein_labels_by_interaction_type`([effect, ...])	Retrieves the entities involved in interactions matching the criteria.
`protein_labels_by_interaction_type_and_data_model`([...])	Retrieves the entities involved in interactions matching the criteria.
`protein_labels_by_interaction_type_and_data_model_and_resource`([...])	Retrieves the entities involved in interactions matching the criteria.
`protein_labels_by_reference`([effect, ...])	Retrieves the entities involved in interactions matching the criteria.
`protein_labels_by_resource`([effect, ...])	Retrieves the entities involved in interactions matching the criteria.
`proteins_by_data_model`([effect, resources, ...])	Retrieves the entities involved in interactions matching the criteria.
`proteins_by_interaction_type`([effect, ...])	Retrieves the entities involved in interactions matching the criteria.
`proteins_by_interaction_type_and_data_model`([...])	Retrieves the entities involved in interactions matching the criteria.
`proteins_by_interaction_type_and_data_model_and_resource`([...])	Retrieves the entities involved in interactions matching the criteria.
`proteins_by_reference`([effect, resources, ...])	Retrieves the entities involved in interactions matching the criteria.
`proteins_by_resource`([effect, resources, ...])	Retrieves the entities involved in interactions matching the criteria.
`reload`()	Reloads the object from the module level.
`resources_a_b`([resources, evidences, ...])	Retrieves the list of resources for the `a_b` direction.
`resources_b_a`([resources, evidences, ...])	Retrieves the list of sources for the `b_a` direction.
`resources_undirected`([resources, evidences, ...])	Retrieves the list of resources without directed information.
`serialize`(**kwargs)	Generates a JSON string with the full contents of the attributes, without any whitespace or line break.
`serialize_attrs`([direction])	Serialize the resource specific attributes into a JSON string.
`serialize_evidences`(direction)	Serialize the evidences into a JSON string.
`small_molecule_identifiers_by_data_model`([...])	Retrieves the entities involved in interactions matching the criteria.
`small_molecule_identifiers_by_interaction_type`([...])	Retrieves the entities involved in interactions matching the criteria.
`small_molecule_identifiers_by_interaction_type_and_data_model`([...])	Retrieves the entities involved in interactions matching the criteria.
`small_molecule_identifiers_by_interaction_type_and_data_model_and_resource`([...])	Retrieves the entities involved in interactions matching the criteria.
`small_molecule_identifiers_by_reference`([...])	Retrieves the entities involved in interactions matching the criteria.
`small_molecule_identifiers_by_resource`([...])	Retrieves the entities involved in interactions matching the criteria.
`small_molecule_labels_by_data_model`([...])	Retrieves the entities involved in interactions matching the criteria.
`small_molecule_labels_by_interaction_type`([...])	Retrieves the entities involved in interactions matching the criteria.
`small_molecule_labels_by_interaction_type_and_data_model`([...])	Retrieves the entities involved in interactions matching the criteria.
`small_molecule_labels_by_interaction_type_and_data_model_and_resource`([...])	Retrieves the entities involved in interactions matching the criteria.
`small_molecule_labels_by_reference`([effect, ...])	Retrieves the entities involved in interactions matching the criteria.
`small_molecule_labels_by_resource`([effect, ...])	Retrieves the entities involved in interactions matching the criteria.
`small_molecules_by_data_model`([effect, ...])	Retrieves the entities involved in interactions matching the criteria.
`small_molecules_by_interaction_type`([...])	Retrieves the entities involved in interactions matching the criteria.
`small_molecules_by_interaction_type_and_data_model`([...])	Retrieves the entities involved in interactions matching the criteria.
`small_molecules_by_interaction_type_and_data_model_and_resource`([...])	Retrieves the entities involved in interactions matching the criteria.
`small_molecules_by_reference`([effect, ...])	Retrieves the entities involved in interactions matching the criteria.
`small_molecules_by_resource`([effect, ...])	Retrieves the entities involved in interactions matching the criteria.
`source`([undirected, resources])	Returns the name(s) of the source node(s) for each existing direction on the interaction.
`sources_reverse`([resources, evidences, ...])	Retrieves the list of sources for the `b_a` direction.
`sources_straight`([resources, evidences, ...])	Retrieves the list of resources for the `a_b` direction.
`sources_undirected`([resources, evidences, ...])	Retrieves the list of resources without directed information.
`src`([undirected, resources])	Returns the name(s) of the source node(s) for each existing direction on the interaction.
`src_by_resource`(resource)	Returns the name(s) of the source node(s) for each existing direction on the interaction for a specific resource.
`target`([undirected, resources])	Returns the name(s) of the target node(s) for each existing direction on the interaction.
`tgt`([undirected, resources])	Returns the name(s) of the target node(s) for each existing direction on the interaction.
`tgt_by_resource`(resource)	Returns the name(s) of the target node(s) for each existing direction on the interaction for a specific resource.
`translate`(ids[, new_attrs])	Translates the node names/identifiers according to the dictionary ids.
`unset_dir`(direction[, only_sign, resource, ...])	Removes directionality and/or source information of the specified direction.
`unset_direction`(direction[, only_sign, ...])	Removes directionality and/or source information of the specified direction.
`unset_interaction_type`(interaction_type)	Removes all evidences with a certain `interaction_type`.
`unset_sign`(direction, sign[, resource, ...])	Removes sign and/or source information of the specified direction and sign.
`update_attrs`([attrs])	Updates the attributes stored here.
`which_directions`([resources, effect])	Returns the pair(s) of nodes for which there is information about their directionality.
`which_dirs`([resources, effect])	Returns the pair(s) of nodes for which there is information about their directionality.
`which_signs`([resources, effect])	Returns the pair(s) of nodes for which there is information about their effect signs.

Attributes

`a`
`b`
`a_b`
`b_a`
`nodes`
`key`
`evidences`
`direction`
`positive`
`negative`
`unknown_effect`
`attrs`
`count_data_models`	Retrieves data models matching the criteria.
`count_degrees_directed`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`count_degrees_directed_in`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`count_degrees_directed_out`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`count_degrees_negative`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`count_degrees_negative_in`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`count_degrees_negative_out`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`count_degrees_non_directed`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`count_degrees_positive`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`count_degrees_positive_in`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`count_degrees_positive_out`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`count_degrees_signed`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`count_degrees_signed_in`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`count_degrees_signed_out`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`count_degrees_undirected`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`count_interaction_types`	Retrieves interaction types matching the criteria.
`count_references`	Retrieves references matching the criteria.
`count_resource_names`	Retrieves resource names matching the criteria.
`count_resource_names_via`	Retrieves resource names via matching the criteria.
`count_resources`	Retrieves resources matching the criteria.
`count_resources_via`	Retrieves resources via matching the criteria.
`data_models`
`data_models_by_data_model`	Retrieves data models matching the criteria.
`data_models_by_interaction_type`	Retrieves data models matching the criteria.
`data_models_by_interaction_type_and_data_model`	Retrieves data models matching the criteria.
`data_models_by_interaction_type_and_data_model_and_resource`	Retrieves data models matching the criteria.
`data_models_by_reference`	Retrieves data models matching the criteria.
`data_models_by_resource`	Retrieves data models matching the criteria.
`datasets_by_data_model`	Retrieves datasets matching the criteria.
`datasets_by_interaction_type`	Retrieves datasets matching the criteria.
`datasets_by_interaction_type_and_data_model`	Retrieves datasets matching the criteria.
`datasets_by_interaction_type_and_data_model_and_resource`	Retrieves datasets matching the criteria.
`datasets_by_reference`	Retrieves datasets matching the criteria.
`datasets_by_resource`	Retrieves datasets matching the criteria.
`degrees_directed_by_data_model`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_directed_by_interaction_type`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_directed_by_interaction_type_and_data_model`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_directed_by_interaction_type_and_data_model_and_resource`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_directed_by_reference`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_directed_by_resource`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_directed_in_by_data_model`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_directed_in_by_interaction_type`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_directed_in_by_interaction_type_and_data_model`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_directed_in_by_interaction_type_and_data_model_and_resource`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_directed_in_by_reference`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_directed_in_by_resource`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_directed_out_by_data_model`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_directed_out_by_interaction_type`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_directed_out_by_interaction_type_and_data_model`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_directed_out_by_interaction_type_and_data_model_and_resource`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_directed_out_by_reference`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_directed_out_by_resource`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_negative_by_data_model`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_negative_by_interaction_type`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_negative_by_interaction_type_and_data_model`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_negative_by_interaction_type_and_data_model_and_resource`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_negative_by_reference`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_negative_by_resource`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_negative_in_by_data_model`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_negative_in_by_interaction_type`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_negative_in_by_interaction_type_and_data_model`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_negative_in_by_interaction_type_and_data_model_and_resource`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_negative_in_by_reference`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_negative_in_by_resource`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_negative_out_by_data_model`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_negative_out_by_interaction_type`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_negative_out_by_interaction_type_and_data_model`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_negative_out_by_interaction_type_and_data_model_and_resource`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_negative_out_by_reference`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_negative_out_by_resource`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_non_directed_by_data_model`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_non_directed_by_interaction_type`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_non_directed_by_interaction_type_and_data_model`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_non_directed_by_interaction_type_and_data_model_and_resource`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_non_directed_by_reference`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_non_directed_by_resource`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_positive_by_data_model`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_positive_by_interaction_type`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_positive_by_interaction_type_and_data_model`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_positive_by_interaction_type_and_data_model_and_resource`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_positive_by_reference`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_positive_by_resource`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_positive_in_by_data_model`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_positive_in_by_interaction_type`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_positive_in_by_interaction_type_and_data_model`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_positive_in_by_interaction_type_and_data_model_and_resource`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_positive_in_by_reference`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_positive_in_by_resource`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_positive_out_by_data_model`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_positive_out_by_interaction_type`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_positive_out_by_interaction_type_and_data_model`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_positive_out_by_interaction_type_and_data_model_and_resource`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_positive_out_by_reference`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_positive_out_by_resource`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_signed_by_data_model`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_signed_by_interaction_type`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_signed_by_interaction_type_and_data_model`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_signed_by_interaction_type_and_data_model_and_resource`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_signed_by_reference`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_signed_by_resource`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_signed_in_by_data_model`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_signed_in_by_interaction_type`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_signed_in_by_interaction_type_and_data_model`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_signed_in_by_interaction_type_and_data_model_and_resource`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_signed_in_by_reference`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_signed_in_by_resource`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_signed_out_by_data_model`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_signed_out_by_interaction_type`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_signed_out_by_interaction_type_and_data_model`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_signed_out_by_interaction_type_and_data_model_and_resource`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_signed_out_by_reference`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_signed_out_by_resource`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_undirected_by_data_model`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_undirected_by_interaction_type`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_undirected_by_interaction_type_and_data_model`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_undirected_by_interaction_type_and_data_model_and_resource`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_undirected_by_reference`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`degrees_undirected_by_resource`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`get_data_models`	Retrieves data models matching the criteria.
`get_datasets`	Retrieves datasets matching the criteria.
`get_degrees_directed`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`get_degrees_directed_in`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`get_degrees_directed_out`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`get_degrees_negative`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`get_degrees_negative_in`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`get_degrees_negative_out`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`get_degrees_non_directed`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`get_degrees_positive`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`get_degrees_positive_in`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`get_degrees_positive_out`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`get_degrees_signed`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`get_degrees_signed_in`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`get_degrees_signed_out`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`get_degrees_undirected`	Returns a set of nodes with the connections matching the direction, effect and evidence criteria.
`get_interaction_types`	Retrieves interaction types matching the criteria.
`get_references`	Retrieves references matching the criteria.
`get_resource_names`	Retrieves resource names matching the criteria.
`get_resource_names_via`	Retrieves resource names via matching the criteria.
`get_resources`	Retrieves resources matching the criteria.
`get_resources_via`	Retrieves resources via matching the criteria.
`interaction_types_by_data_model`	Retrieves interaction types matching the criteria.
`interaction_types_by_interaction_type`	Retrieves interaction types matching the criteria.
`interaction_types_by_interaction_type_and_data_model`	Retrieves interaction types matching the criteria.
`interaction_types_by_interaction_type_and_data_model_and_resource`	Retrieves interaction types matching the criteria.
`interaction_types_by_reference`	Retrieves interaction types matching the criteria.
`interaction_types_by_resource`	Retrieves interaction types matching the criteria.
`references_by_data_model`	Retrieves references matching the criteria.
`references_by_interaction_type`	Retrieves references matching the criteria.
`references_by_interaction_type_and_data_model`	Retrieves references matching the criteria.
`references_by_interaction_type_and_data_model_and_resource`	Retrieves references matching the criteria.
`references_by_reference`	Retrieves references matching the criteria.
`references_by_resource`	Retrieves references matching the criteria.
`resource_names_by_data_model`	Retrieves resource names matching the criteria.
`resource_names_by_interaction_type`	Retrieves resource names matching the criteria.
`resource_names_by_interaction_type_and_data_model`	Retrieves resource names matching the criteria.
`resource_names_by_interaction_type_and_data_model_and_resource`	Retrieves resource names matching the criteria.
`resource_names_by_reference`	Retrieves resource names matching the criteria.
`resource_names_by_resource`	Retrieves resource names matching the criteria.
`resource_names_via_by_data_model`	Retrieves resource names via matching the criteria.
`resource_names_via_by_interaction_type`	Retrieves resource names via matching the criteria.
`resource_names_via_by_interaction_type_and_data_model`	Retrieves resource names via matching the criteria.
`resource_names_via_by_interaction_type_and_data_model_and_resource`	Retrieves resource names via matching the criteria.
`resource_names_via_by_reference`	Retrieves resource names via matching the criteria.
`resource_names_via_by_resource`	Retrieves resource names via matching the criteria.
`resources_by_data_model`	Retrieves resources matching the criteria.
`resources_by_interaction_type`	Retrieves resources matching the criteria.
`resources_by_interaction_type_and_data_model`	Retrieves resources matching the criteria.
`resources_by_interaction_type_and_data_model_and_resource`	Retrieves resources matching the criteria.
`resources_by_reference`	Retrieves resources matching the criteria.
`resources_by_resource`	Retrieves resources matching the criteria.
`resources_via_by_data_model`	Retrieves resources via matching the criteria.
`resources_via_by_interaction_type`	Retrieves resources via matching the criteria.
`resources_via_by_interaction_type_and_data_model`	Retrieves resources via matching the criteria.
`resources_via_by_interaction_type_and_data_model_and_resource`	Retrieves resources via matching the criteria.
`resources_via_by_reference`	Retrieves resources via matching the criteria.
`resources_via_by_resource`	Retrieves resources via matching the criteria.

add_evidence(evidence, direction='undirected', effect=None, references=None, attrs=None)[source]§

Adds directionality information with the corresponding data source named. Modifies self attributes dirs and sources.

Parameters:

evidence (resource.NetworkResource,evidence.Evidence) – Either a pypath.evidence.Evidence object or a resource as pypath.resource.NetworkResource object. In the latter case the references can be provided in a separate argument.
direction (tuple) – Or [str], the directionality key for which the value on dirs has to be set True.
effect (int) – The causal effect of the interaction. 1 or ‘stimulation’ corresponds to a stimulatory, -1 or ‘inhibition’ to an inhibitory while 0 to an unknown or neutral effect.
references (set,NoneType) – A set of references, used only if the resource have been provided as NetworkResource object.
attrs (dict) – Custom (resource specific) attributes.

Sets sign and source information on a given direction of the edge. Modifies the attributes positive and positive_sources or negative and negative_sources depending on the sign. Direction is also updated accordingly, which also modifies the attributes dirs and sources.

Args

direction:: Pair of edge nodes specifying the direction from which the information is to be set/updated.
sign:: Specifies the type of interaction. Either 'positive' or 'negative'.
resource:: Contains the name(s) of the source(s) from which the information was obtained.
attrs:: Custom (resource specific) edge attributes.
kwargs:: Passed to pypath.resource.NetworkResource if resource is not already a NetworkResource or Evidence instance.

asdict(direction: tuple) → dict[source]§: Dictionary representation of the evidences.

complex_identifiers_by_data_model(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Retrieves the entities involved in interactions matching the criteria. It either returns both interacting entities in a set or an empty set. This may not sound so useful at the level of this object but becomes more useful once we want to collect entities having certain kind of interactions across a series of Interaction objects.

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

complex_identifiers_by_interaction_type(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

complex_identifiers_by_interaction_type_and_data_model(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

complex_identifiers_by_interaction_type_and_data_model_and_resource(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

complex_identifiers_by_reference(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

complex_identifiers_by_resource(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

complex_labels_by_data_model(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

complex_labels_by_interaction_type(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

complex_labels_by_interaction_type_and_data_model(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

complex_labels_by_interaction_type_and_data_model_and_resource(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

complex_labels_by_reference(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

complex_labels_by_resource(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

complexes_by_data_model(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

complexes_by_interaction_type(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

complexes_by_interaction_type_and_data_model(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

complexes_by_interaction_type_and_data_model_and_resource(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

complexes_by_reference(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

complexes_by_resource(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

consensus(only_interaction_type=None, only_primary=False, by_references=False, by_reference_resource_pairs=True)[source]§

Infers the consensus edge(s) according to the number of supporting sources. This includes direction and sign.

Returns:: (list) – Contains the consensus edge(s) along with the consensus sign. If there is no major directionality, both are returned. The structure is as follows: ['<source>', '<target>', '<(un)directed>', '<sign>']

consensus_edges(only_interaction_type=None, only_primary=False, by_references=False, by_reference_resource_pairs=True)§

Infers the consensus edge(s) according to the number of supporting sources. This includes direction and sign.

Returns:: (list) – Contains the consensus edge(s) along with the consensus sign. If there is no major directionality, both are returned. The structure is as follows: ['<source>', '<target>', '<(un)directed>', '<sign>']

count_complex_identifiers(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

count_complex_labels(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

count_complexes(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

count_data_models§: Retrieves data models matching the criteria.

count_degrees_directed§

Returns a set of nodes with the connections matching the direction, effect and evidence criteria. E.g. if the query concerns the incoming degrees with positive effect and the matching evidences show A activates B, but not the other way around, only “B” will be returned.

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

count_degrees_directed_in§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

count_degrees_directed_out§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

count_degrees_negative§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

count_degrees_negative_in§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

count_degrees_negative_out§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

count_degrees_non_directed§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

count_degrees_positive§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

count_degrees_positive_in§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

count_degrees_positive_out§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

count_degrees_signed§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

count_degrees_signed_in§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

count_degrees_signed_out§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

count_degrees_undirected§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

count_entities(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

count_identifiers(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

count_interaction_types§: Retrieves interaction types matching the criteria.

count_interactions(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Returns one or two tuples of the interacting partners: one if only one direction, two if both directions match the query criteria. The tuple will be empty if no evidence matches the criteria.

Parameters:

direction (NontType,bool,tuple) – If None both undirected and directed, if True only directed, if a tuple of entities only the interactions with that specific direction will be considered. Unless you set this parameter to True this method will return both directions if one or more undirected resources present. If False, only the undirected interactions will be considered, and if any resource annotates this interaction as undirected both directions will be returned. However the count_interactions_undirected method will return 1 in this case.
effect (NoneType,bool,str) – If None also interactions without effect, if True only the ones with any effect, if a string naming an effect only the interactions with that specific effect will be considered.
resources (NontType,str,set) – Optionally limit the query to one or more resources.
data_model (NontType,str,set) – Optionally limit the query to one or more data models e.g. activity_flow.
interaction_type (NontType,str,set) – Optionally limit the query to one or more interaction types e.g. PPI.
via (NontType,bool,str,set) – Optionally limit the query to certain secondary databases or if False consider only data from primary databases.
entity_type (str) – Molecule type for both of the entities.
source_entity_type (str) – Molecule type for the source entity.
target_entity_type (str) – Molecule type for the target entity.

count_interactions_0(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§: Returns unique interacting pairs without being aware of the direction.

count_interactions_directed(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Args

kwargs:: See the docs of method get_interactions.

count_interactions_mutual(**kwargs)[source]§

Note: undirected interactions does not count as mutual but only interactions with explicit direction information for both directions.

Args

kwargs:: See the docs of method get_interactions.

count_interactions_negative(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Args

kwargs:: See the docs of method get_interactions.

count_interactions_non_directed(**kwargs)[source]§

Returns True if any resource annotates this interaction without and no resource with direction.

Args

kwargs:: See the docs of method get_interactions.

count_interactions_positive(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Args

kwargs:: See the docs of method get_interactions.

count_interactions_signed(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Args

kwargs:: See the docs of method get_interactions.

count_interactions_undirected(**kwargs)[source]§

Returns True if any resource annotates this interaction without direction.

Args

kwargs:: See the docs of method get_interactions.

count_labels(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

count_lncrna_identifiers(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

count_lncrna_labels(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

count_lncrnas(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

count_mirna_identifiers(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

count_mirna_labels(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

count_mirnas(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

count_protein_identifiers(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

count_protein_labels(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

count_proteins(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

count_references§: Retrieves references matching the criteria.

count_resource_names§: Retrieves resource names matching the criteria.

count_resource_names_via§: Retrieves resource names via matching the criteria.

count_resources§: Retrieves resources matching the criteria.

count_resources_via§: Retrieves resources via matching the criteria.

count_small_molecule_identifiers(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

count_small_molecule_labels(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

count_small_molecules(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

data_models_by_data_model§: Retrieves data models matching the criteria.

data_models_by_interaction_type§: Retrieves data models matching the criteria.

data_models_by_interaction_type_and_data_model§: Retrieves data models matching the criteria.

data_models_by_interaction_type_and_data_model_and_resource§: Retrieves data models matching the criteria.

data_models_by_reference§: Retrieves data models matching the criteria.

data_models_by_resource§: Retrieves data models matching the criteria.

datasets_by_data_model§: Retrieves datasets matching the criteria.

datasets_by_interaction_type§: Retrieves datasets matching the criteria.

datasets_by_interaction_type_and_data_model§: Retrieves datasets matching the criteria.

datasets_by_interaction_type_and_data_model_and_resource§: Retrieves datasets matching the criteria.

datasets_by_reference§: Retrieves datasets matching the criteria.

datasets_by_resource§: Retrieves datasets matching the criteria.

degrees_directed_by_data_model§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_directed_by_interaction_type§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_directed_by_interaction_type_and_data_model§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_directed_by_interaction_type_and_data_model_and_resource§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_directed_by_reference§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_directed_by_resource§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_directed_in_by_data_model§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_directed_in_by_interaction_type§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_directed_in_by_interaction_type_and_data_model§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_directed_in_by_interaction_type_and_data_model_and_resource§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_directed_in_by_reference§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_directed_in_by_resource§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_directed_out_by_data_model§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_directed_out_by_interaction_type§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_directed_out_by_interaction_type_and_data_model§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_directed_out_by_interaction_type_and_data_model_and_resource§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_directed_out_by_reference§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_directed_out_by_resource§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_negative_by_data_model§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_negative_by_interaction_type§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_negative_by_interaction_type_and_data_model§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_negative_by_interaction_type_and_data_model_and_resource§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_negative_by_reference§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_negative_by_resource§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_negative_in_by_data_model§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_negative_in_by_interaction_type§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_negative_in_by_interaction_type_and_data_model§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_negative_in_by_interaction_type_and_data_model_and_resource§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_negative_in_by_reference§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_negative_in_by_resource§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_negative_out_by_data_model§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_negative_out_by_interaction_type§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_negative_out_by_interaction_type_and_data_model§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_negative_out_by_interaction_type_and_data_model_and_resource§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_negative_out_by_reference§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_negative_out_by_resource§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_non_directed_by_data_model§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_non_directed_by_interaction_type§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_non_directed_by_interaction_type_and_data_model§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_non_directed_by_interaction_type_and_data_model_and_resource§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_non_directed_by_reference§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_non_directed_by_resource§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_positive_by_data_model§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_positive_by_interaction_type§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_positive_by_interaction_type_and_data_model§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_positive_by_interaction_type_and_data_model_and_resource§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_positive_by_reference§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_positive_by_resource§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_positive_in_by_data_model§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_positive_in_by_interaction_type§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_positive_in_by_interaction_type_and_data_model§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_positive_in_by_interaction_type_and_data_model_and_resource§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_positive_in_by_reference§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_positive_in_by_resource§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_positive_out_by_data_model§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_positive_out_by_interaction_type§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_positive_out_by_interaction_type_and_data_model§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_positive_out_by_interaction_type_and_data_model_and_resource§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_positive_out_by_reference§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_positive_out_by_resource§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_signed_by_data_model§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_signed_by_interaction_type§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_signed_by_interaction_type_and_data_model§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_signed_by_interaction_type_and_data_model_and_resource§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_signed_by_reference§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_signed_by_resource§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_signed_in_by_data_model§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_signed_in_by_interaction_type§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_signed_in_by_interaction_type_and_data_model§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_signed_in_by_interaction_type_and_data_model_and_resource§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_signed_in_by_reference§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_signed_in_by_resource§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_signed_out_by_data_model§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_signed_out_by_interaction_type§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_signed_out_by_interaction_type_and_data_model§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_signed_out_by_interaction_type_and_data_model_and_resource§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_signed_out_by_reference§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_signed_out_by_resource§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_undirected_by_data_model§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_undirected_by_interaction_type§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_undirected_by_interaction_type_and_data_model§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_undirected_by_interaction_type_and_data_model_and_resource§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_undirected_by_reference§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

degrees_undirected_by_resource§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

direction_key(direction)[source]§: The direction keys are tuples of Entity objects; this method creates these tuples from a tuple of strings. The two strings can be labels or identifiers.

dorothea_level(direction: str | tuple) → Literal['A', 'B', 'C', 'D', 'E'][source]§

DoRothEA confidence level for one direction as a single letter.

Some interactions might have multiple levels due to the ambiguous nature of translating gene symbols to UniProt IDs. Here we take the highest level and drop the rest. For interactions without DoRothEA levels None is returned.

dorothea_levels(direction: str | tuple | None = None)[source]§

Retrieves the DoRothEA confidence levels.

Args

direction:: Direction(s) to consider, either a tuple of entities or entity names, or the string undirected.

Returns

List of unique single letter strings representing the five confidence levels (A-E).

entities_by_data_model(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

entities_by_interaction_type(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

entities_by_interaction_type_and_data_model(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

entities_by_interaction_type_and_data_model_and_resource(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

entities_by_reference(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

entities_by_resource(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

evaluate_evidences(this_direction, direction=None, effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None, datasets=None)[source]§: Selects the evidence collections matching the direction and effect criteria and then evaluates if any of the evidences in these collections match the evidence criteria.

generate_df_records(by_source: bool = False, with_references: bool = False)[source]§

Yields interaction records. It is a generator because one edge can be represented by one or more records depending on the signs and directions and other parameters

Args

by_source:: Yield separate records by resources. This way the node pairs will be redundant and you need to group later if you want unique interacting pairs. By default is False because for most applications unique interactions are preferred. If False the refrences field will still be present but with None values.
with_references:: Include the literature references. By default is False because you rarely need these and they increase the data size significantly.

get_attr(resource: str, key: str, direction: str | tuple | None = None)[source]§

Extracts the values of one specific attribute.

Args

resource:: Name of the resource.
key:: Name of the attribute.
direction:: Direction(s) to consider, either a tuple of entities or entity names, or the string undirected.

Returns

Depends on the arguments. The value of the attribute if direction is defined. Otherwise a dict with the value of the attribute for each direction. The value of the attribute is None if the resource or the attribute does not belong to this interaction.

get_complex_identifiers(entity_type=None, direction=None, effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None, return_type=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

get_complex_labels(entity_type=None, direction=None, effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None, return_type=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

get_complexes(entity_type=None, direction=None, effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None, return_type=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

get_data_models§: Retrieves data models matching the criteria.

get_datasets§: Retrieves datasets matching the criteria.

get_degrees(mode: str, direction=None, effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)[source]§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

get_degrees_directed§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

get_degrees_directed_in§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

get_degrees_directed_out§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

get_degrees_negative§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

get_degrees_negative_in§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

get_degrees_negative_out§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

get_degrees_non_directed§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

get_degrees_positive§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

get_degrees_positive_in§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

get_degrees_positive_out§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

get_degrees_signed§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

get_degrees_signed_in§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

get_degrees_signed_out§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

get_degrees_undirected§

Args

mode:: The type of degrees to be considered. Three possible values are 'IN', ‘OUT’` and 'ALL' for incoming, outgoing and all connections, respectively. If the direction is False the only possible mode is ALL. If the direction is None and also directed evidence(s) match the criteria these will overwrite the undirected evidences and only the directed result will be returned.

get_direction(direction, resources=False, evidences=False, sources=False, resource_names=False)[source]§

Returns the state (or resources if specified) of the given direction.

Parameters:

direction (tuple) – Or [str] (if 'undirected'). Pair of nodes from which direction information is to be retrieved.
resources (bool) – Optional, 'False' by default. Specifies if the resources information of the given direction is to be retrieved instead.

Returns:

(bool or set) – (if resources=True). Presence/absence of the requested direction (or the list of resources if specified). Returns None if direction is not valid.

get_directions(src, tgt, resources=False, evidences=False, resource_names=False, sources=False)[source]§

Returns all directions with boolean values or list of sources.

Parameters:

src (str) – Source node.
tgt (str) – Target node.
resources (bool) – Optional, False by default. Specifies whether to return the resources attribute instead of dirs.

Returns:

Contains the dirs (or resources if specified) of the given edge.

get_entities(entity_type=None, direction=None, effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None, datasets=None, return_type=None)[source]§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

get_identifiers(entity_type=None, direction=None, effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None, return_type=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

get_interaction_types§: Retrieves interaction types matching the criteria.

get_interactions(direction=None, effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None, entity_type=None, source_entity_type=None, target_entity_type=None, datasets=None)[source]§

Returns one or two tuples of the interacting partners: one if only one direction, two if both directions match the query criteria. The tuple will be empty if no evidence matches the criteria.

Parameters:

direction (NontType,bool,tuple) – If None both undirected and directed, if True only directed, if a tuple of entities only the interactions with that specific direction will be considered. Unless you set this parameter to True this method will return both directions if one or more undirected resources present. If False, only the undirected interactions will be considered, and if any resource annotates this interaction as undirected both directions will be returned. However the count_interactions_undirected method will return 1 in this case.
effect (NoneType,bool,str) – If None also interactions without effect, if True only the ones with any effect, if a string naming an effect only the interactions with that specific effect will be considered.
resources (NontType,str,set) – Optionally limit the query to one or more resources.
data_model (NontType,str,set) – Optionally limit the query to one or more data models e.g. activity_flow.
interaction_type (NontType,str,set) – Optionally limit the query to one or more interaction types e.g. PPI.
via (NontType,bool,str,set) – Optionally limit the query to certain secondary databases or if False consider only data from primary databases.
entity_type (str) – Molecule type for both of the entities.
source_entity_type (str) – Molecule type for the source entity.
target_entity_type (str) – Molecule type for the target entity.

get_interactions_0(**kwargs)[source]§: Returns unique interacting pairs without being aware of the direction.

get_interactions_directed(**kwargs)[source]§

Args

kwargs:: See the docs of method get_interactions.

get_interactions_mutual(**kwargs)[source]§

Note: undirected interactions does not count as mutual but only interactions with explicit direction information for both directions.

Args

kwargs:: See the docs of method get_interactions.

get_interactions_negative(**kwargs)[source]§

Args

kwargs:: See the docs of method get_interactions.

get_interactions_non_directed(**kwargs)[source]§

Only the undirected interactions will be considered, if any resource annotates this interaction as undirected both directions will be returned, but only if no resource provide direction. However the count_interactions_non_directed method will return 1 in this case.

Args

kwargs:: See the docs of method get_interactions.

get_interactions_non_directed_0(**kwargs)[source]§

Only the undirected interactions will be considered, if any resource annotates this interaction as undirected and none as directed, the interacting pair as a sorted tuple will be returned inside a one element tuple.

Args

kwargs:: See the docs of method get_interactions.

get_interactions_positive(**kwargs)[source]§

Args

kwargs:: See the docs of method get_interactions.

get_interactions_signed(**kwargs)[source]§

Args

kwargs:: See the docs of method get_interactions.

get_interactions_undirected(**kwargs)[source]§

Only the undirected interactions will be considered, if any resource annotates this interaction as undirected both directions will be returned, no matter if certain resources provide direction. However the count_interactions_undirected method will return 1 in this case.

Args

kwargs:: See the docs of method get_interactions.

get_interactions_undirected_0(**kwargs)[source]§

Only the undirected interactions will be considered, if any resource annotates this interaction as undirected the interacting pair as a sorted tuple will be returned inside a one element tuple.

Args

kwargs:: See the docs of method get_interactions.

get_labels(entity_type=None, direction=None, effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None, return_type=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

get_lncrna_identifiers(entity_type=None, direction=None, effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None, return_type=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

get_lncrna_labels(entity_type=None, direction=None, effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None, return_type=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

get_lncrnas(entity_type=None, direction=None, effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None, return_type=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

get_mirna_identifiers(entity_type=None, direction=None, effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None, return_type=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

get_mirna_labels(entity_type=None, direction=None, effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None, return_type=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

get_mirnas(entity_type=None, direction=None, effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None, return_type=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

get_protein_identifiers(entity_type=None, direction=None, effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None, return_type=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

get_protein_labels(entity_type=None, direction=None, effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None, return_type=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

get_proteins(entity_type=None, direction=None, effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None, return_type=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

get_references§: Retrieves references matching the criteria.

get_resource_names§: Retrieves resource names matching the criteria.

get_resource_names_via§: Retrieves resource names via matching the criteria.

get_resources§: Retrieves resources matching the criteria.

get_resources_via§: Retrieves resources via matching the criteria.

get_sign(direction: tuple, sign: str | None = None, evidences: bool = False, resources: bool = False, resource_names: bool = False, sources: bool = False) → list[bool | str][source]§

Retrieves the sign information of the edge in the given diretion. If specified in sign, only that sign’s information will be retrieved. If specified in sources, the sources of that information will be retrieved instead.

Args

direction:: Contains the pair of nodes specifying the directionality of the edge from which th information is to be retrieved.
sign:: Optional, None by default. Denotes whether to retrieve the 'positive' or 'negative' specific information.
resources:: Optional, False by default. Specifies whether to return the resources instead of sign.

Returns

If sign=None containing [bool] values denoting the presence of positive and negative sign on that direction, if sources=True the [set] of sources for each of them will be returned instead. If sign is specified, returns [bool] or [set] (if sources=True) of that specific direction and sign.

get_small_molecule_identifiers(entity_type=None, direction=None, effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None, return_type=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

get_small_molecule_labels(entity_type=None, direction=None, effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None, return_type=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

get_small_molecules(entity_type=None, direction=None, effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None, return_type=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

has_sign(direction=None, resources=None)[source]§

Checks whether the edge (or for a specific direction) has any signed information (about positive/negative interactions).

Parameters:

direction (tuple) – Optional, None by default. If specified, only the information of that direction is checked for sign.

Returns:

(bool) – True if there exist any information on the: sign of the interaction, False otherwise.

identifiers_by_data_model(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

identifiers_by_interaction_type(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

identifiers_by_interaction_type_and_data_model(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

identifiers_by_interaction_type_and_data_model_and_resource(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

identifiers_by_reference(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

identifiers_by_resource(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

interaction_types_by_data_model§: Retrieves interaction types matching the criteria.

interaction_types_by_interaction_type§: Retrieves interaction types matching the criteria.

interaction_types_by_interaction_type_and_data_model§: Retrieves interaction types matching the criteria.

interaction_types_by_interaction_type_and_data_model_and_resource§: Retrieves interaction types matching the criteria.

interaction_types_by_reference§: Retrieves interaction types matching the criteria.

interaction_types_by_resource§: Retrieves interaction types matching the criteria.

interactions_0_by_data_model(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§: Returns unique interacting pairs without being aware of the direction.

interactions_0_by_interaction_type(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§: Returns unique interacting pairs without being aware of the direction.

interactions_0_by_interaction_type_and_data_model(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§: Returns unique interacting pairs without being aware of the direction.

interactions_0_by_interaction_type_and_data_model_and_resource(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§: Returns unique interacting pairs without being aware of the direction.

interactions_0_by_reference(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§: Returns unique interacting pairs without being aware of the direction.

interactions_0_by_resource(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§: Returns unique interacting pairs without being aware of the direction.

interactions_by_data_model(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Returns one or two tuples of the interacting partners: one if only one direction, two if both directions match the query criteria. The tuple will be empty if no evidence matches the criteria.

Parameters:

direction (NontType,bool,tuple) – If None both undirected and directed, if True only directed, if a tuple of entities only the interactions with that specific direction will be considered. Unless you set this parameter to True this method will return both directions if one or more undirected resources present. If False, only the undirected interactions will be considered, and if any resource annotates this interaction as undirected both directions will be returned. However the count_interactions_undirected method will return 1 in this case.
effect (NoneType,bool,str) – If None also interactions without effect, if True only the ones with any effect, if a string naming an effect only the interactions with that specific effect will be considered.
resources (NontType,str,set) – Optionally limit the query to one or more resources.
data_model (NontType,str,set) – Optionally limit the query to one or more data models e.g. activity_flow.
interaction_type (NontType,str,set) – Optionally limit the query to one or more interaction types e.g. PPI.
via (NontType,bool,str,set) – Optionally limit the query to certain secondary databases or if False consider only data from primary databases.
entity_type (str) – Molecule type for both of the entities.
source_entity_type (str) – Molecule type for the source entity.
target_entity_type (str) – Molecule type for the target entity.

interactions_by_interaction_type(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Returns one or two tuples of the interacting partners: one if only one direction, two if both directions match the query criteria. The tuple will be empty if no evidence matches the criteria.

Parameters:

direction (NontType,bool,tuple) – If None both undirected and directed, if True only directed, if a tuple of entities only the interactions with that specific direction will be considered. Unless you set this parameter to True this method will return both directions if one or more undirected resources present. If False, only the undirected interactions will be considered, and if any resource annotates this interaction as undirected both directions will be returned. However the count_interactions_undirected method will return 1 in this case.
effect (NoneType,bool,str) – If None also interactions without effect, if True only the ones with any effect, if a string naming an effect only the interactions with that specific effect will be considered.
resources (NontType,str,set) – Optionally limit the query to one or more resources.
data_model (NontType,str,set) – Optionally limit the query to one or more data models e.g. activity_flow.
interaction_type (NontType,str,set) – Optionally limit the query to one or more interaction types e.g. PPI.
via (NontType,bool,str,set) – Optionally limit the query to certain secondary databases or if False consider only data from primary databases.
entity_type (str) – Molecule type for both of the entities.
source_entity_type (str) – Molecule type for the source entity.
target_entity_type (str) – Molecule type for the target entity.

interactions_by_interaction_type_and_data_model(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Returns one or two tuples of the interacting partners: one if only one direction, two if both directions match the query criteria. The tuple will be empty if no evidence matches the criteria.

Parameters:

direction (NontType,bool,tuple) – If None both undirected and directed, if True only directed, if a tuple of entities only the interactions with that specific direction will be considered. Unless you set this parameter to True this method will return both directions if one or more undirected resources present. If False, only the undirected interactions will be considered, and if any resource annotates this interaction as undirected both directions will be returned. However the count_interactions_undirected method will return 1 in this case.
effect (NoneType,bool,str) – If None also interactions without effect, if True only the ones with any effect, if a string naming an effect only the interactions with that specific effect will be considered.
resources (NontType,str,set) – Optionally limit the query to one or more resources.
data_model (NontType,str,set) – Optionally limit the query to one or more data models e.g. activity_flow.
interaction_type (NontType,str,set) – Optionally limit the query to one or more interaction types e.g. PPI.
via (NontType,bool,str,set) – Optionally limit the query to certain secondary databases or if False consider only data from primary databases.
entity_type (str) – Molecule type for both of the entities.
source_entity_type (str) – Molecule type for the source entity.
target_entity_type (str) – Molecule type for the target entity.

interactions_by_interaction_type_and_data_model_and_resource(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Returns one or two tuples of the interacting partners: one if only one direction, two if both directions match the query criteria. The tuple will be empty if no evidence matches the criteria.

Parameters:

direction (NontType,bool,tuple) – If None both undirected and directed, if True only directed, if a tuple of entities only the interactions with that specific direction will be considered. Unless you set this parameter to True this method will return both directions if one or more undirected resources present. If False, only the undirected interactions will be considered, and if any resource annotates this interaction as undirected both directions will be returned. However the count_interactions_undirected method will return 1 in this case.
effect (NoneType,bool,str) – If None also interactions without effect, if True only the ones with any effect, if a string naming an effect only the interactions with that specific effect will be considered.
resources (NontType,str,set) – Optionally limit the query to one or more resources.
data_model (NontType,str,set) – Optionally limit the query to one or more data models e.g. activity_flow.
interaction_type (NontType,str,set) – Optionally limit the query to one or more interaction types e.g. PPI.
via (NontType,bool,str,set) – Optionally limit the query to certain secondary databases or if False consider only data from primary databases.
entity_type (str) – Molecule type for both of the entities.
source_entity_type (str) – Molecule type for the source entity.
target_entity_type (str) – Molecule type for the target entity.

interactions_by_reference(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Returns one or two tuples of the interacting partners: one if only one direction, two if both directions match the query criteria. The tuple will be empty if no evidence matches the criteria.

Parameters:

direction (NontType,bool,tuple) – If None both undirected and directed, if True only directed, if a tuple of entities only the interactions with that specific direction will be considered. Unless you set this parameter to True this method will return both directions if one or more undirected resources present. If False, only the undirected interactions will be considered, and if any resource annotates this interaction as undirected both directions will be returned. However the count_interactions_undirected method will return 1 in this case.
effect (NoneType,bool,str) – If None also interactions without effect, if True only the ones with any effect, if a string naming an effect only the interactions with that specific effect will be considered.
resources (NontType,str,set) – Optionally limit the query to one or more resources.
data_model (NontType,str,set) – Optionally limit the query to one or more data models e.g. activity_flow.
interaction_type (NontType,str,set) – Optionally limit the query to one or more interaction types e.g. PPI.
via (NontType,bool,str,set) – Optionally limit the query to certain secondary databases or if False consider only data from primary databases.
entity_type (str) – Molecule type for both of the entities.
source_entity_type (str) – Molecule type for the source entity.
target_entity_type (str) – Molecule type for the target entity.

interactions_by_resource(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Returns one or two tuples of the interacting partners: one if only one direction, two if both directions match the query criteria. The tuple will be empty if no evidence matches the criteria.

Parameters:

direction (NontType,bool,tuple) – If None both undirected and directed, if True only directed, if a tuple of entities only the interactions with that specific direction will be considered. Unless you set this parameter to True this method will return both directions if one or more undirected resources present. If False, only the undirected interactions will be considered, and if any resource annotates this interaction as undirected both directions will be returned. However the count_interactions_undirected method will return 1 in this case.
effect (NoneType,bool,str) – If None also interactions without effect, if True only the ones with any effect, if a string naming an effect only the interactions with that specific effect will be considered.
resources (NontType,str,set) – Optionally limit the query to one or more resources.
data_model (NontType,str,set) – Optionally limit the query to one or more data models e.g. activity_flow.
interaction_type (NontType,str,set) – Optionally limit the query to one or more interaction types e.g. PPI.
via (NontType,bool,str,set) – Optionally limit the query to certain secondary databases or if False consider only data from primary databases.
entity_type (str) – Molecule type for both of the entities.
source_entity_type (str) – Molecule type for the source entity.
target_entity_type (str) – Molecule type for the target entity.

interactions_directed_by_data_model(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Args

kwargs:: See the docs of method get_interactions.

interactions_directed_by_interaction_type(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Args

kwargs:: See the docs of method get_interactions.

interactions_directed_by_interaction_type_and_data_model(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Args

kwargs:: See the docs of method get_interactions.

interactions_directed_by_interaction_type_and_data_model_and_resource(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Args

kwargs:: See the docs of method get_interactions.

interactions_directed_by_reference(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Args

kwargs:: See the docs of method get_interactions.

interactions_directed_by_resource(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Args

kwargs:: See the docs of method get_interactions.

interactions_mutual_by_data_model(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Note: undirected interactions does not count as mutual but only interactions with explicit direction information for both directions.

Args

kwargs:: See the docs of method get_interactions.

interactions_mutual_by_interaction_type(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Note: undirected interactions does not count as mutual but only interactions with explicit direction information for both directions.

Args

kwargs:: See the docs of method get_interactions.

interactions_mutual_by_interaction_type_and_data_model(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Note: undirected interactions does not count as mutual but only interactions with explicit direction information for both directions.

Args

kwargs:: See the docs of method get_interactions.

interactions_mutual_by_interaction_type_and_data_model_and_resource(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Note: undirected interactions does not count as mutual but only interactions with explicit direction information for both directions.

Args

kwargs:: See the docs of method get_interactions.

interactions_mutual_by_reference(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Note: undirected interactions does not count as mutual but only interactions with explicit direction information for both directions.

Args

kwargs:: See the docs of method get_interactions.

interactions_mutual_by_resource(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Note: undirected interactions does not count as mutual but only interactions with explicit direction information for both directions.

Args

kwargs:: See the docs of method get_interactions.

interactions_negative_by_data_model(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Args

kwargs:: See the docs of method get_interactions.

interactions_negative_by_interaction_type(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Args

kwargs:: See the docs of method get_interactions.

interactions_negative_by_interaction_type_and_data_model(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Args

kwargs:: See the docs of method get_interactions.

interactions_negative_by_interaction_type_and_data_model_and_resource(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Args

kwargs:: See the docs of method get_interactions.

interactions_negative_by_reference(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Args

kwargs:: See the docs of method get_interactions.

interactions_negative_by_resource(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Args

kwargs:: See the docs of method get_interactions.

interactions_non_directed_0_by_data_model(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Args

kwargs:: See the docs of method get_interactions.

interactions_non_directed_0_by_interaction_type(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Args

kwargs:: See the docs of method get_interactions.

interactions_non_directed_0_by_interaction_type_and_data_model(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Args

kwargs:: See the docs of method get_interactions.

interactions_non_directed_0_by_interaction_type_and_data_model_and_resource(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Args

kwargs:: See the docs of method get_interactions.

interactions_non_directed_0_by_reference(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Args

kwargs:: See the docs of method get_interactions.

interactions_non_directed_0_by_resource(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Args

kwargs:: See the docs of method get_interactions.

interactions_non_directed_by_data_model(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Args

kwargs:: See the docs of method get_interactions.

interactions_non_directed_by_interaction_type(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Args

kwargs:: See the docs of method get_interactions.

interactions_non_directed_by_interaction_type_and_data_model(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Args

kwargs:: See the docs of method get_interactions.

interactions_non_directed_by_interaction_type_and_data_model_and_resource(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Args

kwargs:: See the docs of method get_interactions.

interactions_non_directed_by_reference(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Args

kwargs:: See the docs of method get_interactions.

interactions_non_directed_by_resource(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Args

kwargs:: See the docs of method get_interactions.

interactions_positive_by_data_model(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Args

kwargs:: See the docs of method get_interactions.

interactions_positive_by_interaction_type(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Args

kwargs:: See the docs of method get_interactions.

interactions_positive_by_interaction_type_and_data_model(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Args

kwargs:: See the docs of method get_interactions.

interactions_positive_by_interaction_type_and_data_model_and_resource(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Args

kwargs:: See the docs of method get_interactions.

interactions_positive_by_reference(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Args

kwargs:: See the docs of method get_interactions.

interactions_positive_by_resource(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Args

kwargs:: See the docs of method get_interactions.

interactions_signed_by_data_model(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Args

kwargs:: See the docs of method get_interactions.

interactions_signed_by_interaction_type(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Args

kwargs:: See the docs of method get_interactions.

interactions_signed_by_interaction_type_and_data_model(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Args

kwargs:: See the docs of method get_interactions.

interactions_signed_by_interaction_type_and_data_model_and_resource(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Args

kwargs:: See the docs of method get_interactions.

interactions_signed_by_reference(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Args

kwargs:: See the docs of method get_interactions.

interactions_signed_by_resource(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Args

kwargs:: See the docs of method get_interactions.

interactions_undirected_0_by_data_model(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Only the undirected interactions will be considered, if any resource annotates this interaction as undirected the interacting pair as a sorted tuple will be returned inside a one element tuple.

Args

kwargs:: See the docs of method get_interactions.

interactions_undirected_0_by_interaction_type(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Only the undirected interactions will be considered, if any resource annotates this interaction as undirected the interacting pair as a sorted tuple will be returned inside a one element tuple.

Args

kwargs:: See the docs of method get_interactions.

interactions_undirected_0_by_interaction_type_and_data_model(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Only the undirected interactions will be considered, if any resource annotates this interaction as undirected the interacting pair as a sorted tuple will be returned inside a one element tuple.

Args

kwargs:: See the docs of method get_interactions.

interactions_undirected_0_by_interaction_type_and_data_model_and_resource(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Only the undirected interactions will be considered, if any resource annotates this interaction as undirected the interacting pair as a sorted tuple will be returned inside a one element tuple.

Args

kwargs:: See the docs of method get_interactions.

interactions_undirected_0_by_reference(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Only the undirected interactions will be considered, if any resource annotates this interaction as undirected the interacting pair as a sorted tuple will be returned inside a one element tuple.

Args

kwargs:: See the docs of method get_interactions.

interactions_undirected_0_by_resource(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Only the undirected interactions will be considered, if any resource annotates this interaction as undirected the interacting pair as a sorted tuple will be returned inside a one element tuple.

Args

kwargs:: See the docs of method get_interactions.

interactions_undirected_by_data_model(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Args

kwargs:: See the docs of method get_interactions.

interactions_undirected_by_interaction_type(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Args

kwargs:: See the docs of method get_interactions.

interactions_undirected_by_interaction_type_and_data_model(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Args

kwargs:: See the docs of method get_interactions.

interactions_undirected_by_interaction_type_and_data_model_and_resource(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Args

kwargs:: See the docs of method get_interactions.

interactions_undirected_by_reference(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Args

kwargs:: See the docs of method get_interactions.

interactions_undirected_by_resource(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Args

kwargs:: See the docs of method get_interactions.

is_directed()[source]§

Checks if edge has any directionality information.

Returns:: (bool) – Returns True if any of the dirs attribute values is True (except 'undirected'), False otherwise.

is_directed_by_resources(resources=None)[source]§

Checks if edge has any directionality information from some resource(s).

Returns:: (bool) – Returns True if any of the dirs attribute values is True (except 'undirected'), False otherwise.

is_inhibition(direction=None, resources=None)[source]§

Checks if any (or for a specific direction) interaction is inhibition (negative interaction).

Parameters:: direction (tuple) – Optional, None by default. If specified, checks the negative attribute of that specific directionality. If not specified, checks both.
Returns:: (bool) – True if any interaction (or the specified direction) is inhibitory (negative).

is_loop()[source]§

Returns:

True if the interaction is a loop edge i.e. its endpoints are the same node.

is_mutual(**kwargs)[source]§

Note: undirected interactions does not count as mutual but only interactions with explicit direction information for both directions.

Args

kwargs:: See the docs of method get_interactions.

is_mutual_by_resources(resources=None)[source]§: Checks if the edge has mutual directions (both A–>B and B–>A) according to some resource(s).

is_stimulation(direction=None, resources=None)[source]§

Checks if any (or for a specific direction) interaction is activation (positive interaction).

Parameters:: direction (tuple) – Optional, None by default. If specified, checks the positive attribute of that specific directionality. If not specified, checks both.
Returns:: (bool) – True if any interaction (or the specified direction) is activatory (positive).

iter_evidences(this_direction, direction=None, effect=None)[source]§: Selects and yields evidence collections matching the direction and effect criteria.

iter_match_evidences(this_direction, direction=None, effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None, datasets=None)[source]§: Selects the evidence collections matching the direction and effect criteria and yields collections matching the evidence criteria.

labels_by_data_model(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

labels_by_interaction_type(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

labels_by_interaction_type_and_data_model(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

labels_by_interaction_type_and_data_model_and_resource(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

labels_by_reference(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

labels_by_resource(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

lncrna_identifiers_by_data_model(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

lncrna_identifiers_by_interaction_type(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

lncrna_identifiers_by_interaction_type_and_data_model(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

lncrna_identifiers_by_interaction_type_and_data_model_and_resource(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

lncrna_identifiers_by_reference(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

lncrna_identifiers_by_resource(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

lncrna_labels_by_data_model(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

lncrna_labels_by_interaction_type(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

lncrna_labels_by_interaction_type_and_data_model(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

lncrna_labels_by_interaction_type_and_data_model_and_resource(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

lncrna_labels_by_reference(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

lncrna_labels_by_resource(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

lncrnas_by_data_model(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

lncrnas_by_interaction_type(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

lncrnas_by_interaction_type_and_data_model(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

lncrnas_by_interaction_type_and_data_model_and_resource(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

lncrnas_by_reference(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

lncrnas_by_resource(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

majority_dir(only_interaction_type=None, only_primary=True, by_references=False, by_reference_resource_pairs=True)[source]§

Infers which is the major directionality of the edge by number of supporting sources.

Returns:: (tuple) – Contains the pair of nodes denoting the consensus directionality. If the number of sources on both directions is equal, None is returned. If there is no directionality information, 'undirected'` will be returned.

majority_sign(only_interaction_type=None, only_primary=True, by_references=False, by_reference_resource_pairs=True)[source]§

Infers which is the major sign (activation/inhibition) of the edge by number of supporting sources on both directions.

Returns:: (dict) – Keys are the node tuples on both directions (straight/reverse) and values can be either None if that direction has no sign information or a list of two [bool] elements corresponding to majority of positive and majority of negative support. In case both elements of the list are True, this means the number of supporting sources for both signs in that direction is equal.

merge(other)[source]§

Merges current Interaction with another (if and only if they are the same class and contain the same nodes). Updates the attributes direction, positive and negative.

Parameters:: other (pypath.interaction.Interaction) – The new Interaction object to be merged with the current one.

mirna_identifiers_by_data_model(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

mirna_identifiers_by_interaction_type(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

mirna_identifiers_by_interaction_type_and_data_model(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

mirna_identifiers_by_interaction_type_and_data_model_and_resource(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

mirna_identifiers_by_reference(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

mirna_identifiers_by_resource(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

mirna_labels_by_data_model(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

mirna_labels_by_interaction_type(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

mirna_labels_by_interaction_type_and_data_model(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

mirna_labels_by_interaction_type_and_data_model_and_resource(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

mirna_labels_by_reference(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

mirna_labels_by_resource(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

mirnas_by_data_model(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

mirnas_by_interaction_type(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

mirnas_by_interaction_type_and_data_model(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

mirnas_by_interaction_type_and_data_model_and_resource(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

mirnas_by_reference(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

mirnas_by_resource(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

negative_a_b()[source]§

Checks if the a_b directionality is a negative interaction.

Returns:: (bool) – True if there is supporting information on the a_b direction of the edge as inhibition. False otherwise.

negative_b_a()[source]§

Checks if the b_a directionality is a negative interaction.

Returns:: (bool) – True if there is supporting information on the b_a direction of the edge as inhibition. False otherwise.

negative_resources_a_b(**kwargs)[source]§

Retrieves the list of resources for the a_b direction and negative sign.

Returns:: (set) – Contains the names of the resources supporting the a_b directionality of the edge with a negative sign.

negative_resources_b_a(**kwargs)[source]§

Retrieves the list of resources for the b_a direction and negative sign.

Returns:: (set) – Contains the names of the resources supporting the b_a directionality of the edge with a negative sign.

negative_reverse()§

Checks if the b_a directionality is a negative interaction.

Returns:: (bool) – True if there is supporting information on the b_a direction of the edge as inhibition. False otherwise.

negative_straight()§

Checks if the a_b directionality is a negative interaction.

Returns:: (bool) – True if there is supporting information on the a_b direction of the edge as inhibition. False otherwise.

positive_a_b()[source]§

Checks if the a_b directionality is a positive interaction.

Returns:: (bool) – True if there is supporting information on the a_b direction of the edge as activation. False otherwise.

positive_b_a()[source]§

Checks if the b_a directionality is a positive interaction.

Returns:: (bool) – True if there is supporting information on the b_a direction of the edge as activation. False otherwise.

positive_resources_a_b(**kwargs)[source]§

Retrieves the list of resources for the a_b direction and positive sign.

Returns:: (set) – Contains the names of the resources supporting the a_b directionality of the edge with a positive sign.

positive_resources_b_a(**kwargs)[source]§

Retrieves the list of resources for the b_a direction and positive sign.

Returns:: (set) – Contains the names of the resources supporting the b_a directionality of the edge with a positive sign.

positive_reverse()§

Checks if the b_a directionality is a positive interaction.

Returns:: (bool) – True if there is supporting information on the b_a direction of the edge as activation. False otherwise.

positive_straight()§

Checks if the a_b directionality is a positive interaction.

Returns:: (bool) – True if there is supporting information on the a_b direction of the edge as activation. False otherwise.

protein_identifiers_by_data_model(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

protein_identifiers_by_interaction_type(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

protein_identifiers_by_interaction_type_and_data_model(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

protein_identifiers_by_interaction_type_and_data_model_and_resource(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

protein_identifiers_by_reference(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

protein_identifiers_by_resource(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

protein_labels_by_data_model(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

protein_labels_by_interaction_type(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

protein_labels_by_interaction_type_and_data_model(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

protein_labels_by_interaction_type_and_data_model_and_resource(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

protein_labels_by_reference(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

protein_labels_by_resource(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

proteins_by_data_model(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

proteins_by_interaction_type(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

proteins_by_interaction_type_and_data_model(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

proteins_by_interaction_type_and_data_model_and_resource(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

proteins_by_reference(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

proteins_by_resource(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

references_by_data_model§: Retrieves references matching the criteria.

references_by_interaction_type§: Retrieves references matching the criteria.

references_by_interaction_type_and_data_model§: Retrieves references matching the criteria.

references_by_interaction_type_and_data_model_and_resource§: Retrieves references matching the criteria.

references_by_reference§: Retrieves references matching the criteria.

references_by_resource§: Retrieves references matching the criteria.

reload()[source]§: Reloads the object from the module level.

resource_names_by_data_model§: Retrieves resource names matching the criteria.

resource_names_by_interaction_type§: Retrieves resource names matching the criteria.

resource_names_by_interaction_type_and_data_model§: Retrieves resource names matching the criteria.

resource_names_by_interaction_type_and_data_model_and_resource§: Retrieves resource names matching the criteria.

resource_names_by_reference§: Retrieves resource names matching the criteria.

resource_names_by_resource§: Retrieves resource names matching the criteria.

resource_names_via_by_data_model§: Retrieves resource names via matching the criteria.

resource_names_via_by_interaction_type§: Retrieves resource names via matching the criteria.

resource_names_via_by_interaction_type_and_data_model§: Retrieves resource names via matching the criteria.

resource_names_via_by_interaction_type_and_data_model_and_resource§: Retrieves resource names via matching the criteria.

resource_names_via_by_reference§: Retrieves resource names via matching the criteria.

resource_names_via_by_resource§: Retrieves resource names via matching the criteria.

resources_a_b(resources=False, evidences=False, resource_names=False, sources=False)[source]§

Retrieves the list of resources for the a_b direction.

Returns:: (set) – Contains the names of the sources supporting the a_b directionality of the edge.

resources_b_a(resources=False, evidences=False, resource_names=False, sources=False)[source]§

Retrieves the list of sources for the b_a direction.

Returns:: (set) – Contains the names of the sources supporting the b_a directionality of the edge.

resources_by_data_model§: Retrieves resources matching the criteria.

resources_by_interaction_type§: Retrieves resources matching the criteria.

resources_by_interaction_type_and_data_model§: Retrieves resources matching the criteria.

resources_by_interaction_type_and_data_model_and_resource§: Retrieves resources matching the criteria.

resources_by_reference§: Retrieves resources matching the criteria.

resources_by_resource§: Retrieves resources matching the criteria.

resources_undirected(resources=False, evidences=False, resource_names=False, sources=False)[source]§

Retrieves the list of resources without directed information.

Returns:: (set) – Contains the names of the sources supporting the edge presence but without specific directionality information.

resources_via_by_data_model§: Retrieves resources via matching the criteria.

resources_via_by_interaction_type§: Retrieves resources via matching the criteria.

resources_via_by_interaction_type_and_data_model§: Retrieves resources via matching the criteria.

resources_via_by_interaction_type_and_data_model_and_resource§: Retrieves resources via matching the criteria.

resources_via_by_reference§: Retrieves resources via matching the criteria.

resources_via_by_resource§: Retrieves resources via matching the criteria.

serialize(**kwargs)§

Generates a JSON string with the full contents of the attributes, without any whitespace or line break.

Returns: (str): The attributes JSON serialized.

serialize_attrs(direction: str | tuple | None = None) → str[source]§: Serialize the resource specific attributes into a JSON string.

serialize_evidences(direction: tuple) → str[source]§: Serialize the evidences into a JSON string.

small_molecule_identifiers_by_data_model(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

small_molecule_identifiers_by_interaction_type(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

small_molecule_identifiers_by_interaction_type_and_data_model(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

small_molecule_identifiers_by_interaction_type_and_data_model_and_resource(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

small_molecule_identifiers_by_reference(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

small_molecule_identifiers_by_resource(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

small_molecule_labels_by_data_model(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

small_molecule_labels_by_interaction_type(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

small_molecule_labels_by_interaction_type_and_data_model(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

small_molecule_labels_by_interaction_type_and_data_model_and_resource(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

small_molecule_labels_by_reference(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

small_molecule_labels_by_resource(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

small_molecules_by_data_model(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

small_molecules_by_interaction_type(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

small_molecules_by_interaction_type_and_data_model(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

small_molecules_by_interaction_type_and_data_model_and_resource(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

small_molecules_by_reference(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

small_molecules_by_resource(effect=None, resources=None, data_model=None, interaction_type=None, via=None, references=None)§

Parameters:

entity_type (str) – The type of the molecular entity. Possible values: protein, complex, mirna, small_molecule.
return_type (str) – The type of values to return. Default is py:class:pypath.entity.Entity objects, alternatives are labels identifiers.

source(undirected: bool = False, resources=None, **kwargs)[source]§

Returns the name(s) of the source node(s) for each existing direction on the interaction.

Args

undirected:: Optional, False by default.

Returns

(list) – Contains the name(s) for the source node(s). This means if the interaction is bidirectional, the list will contain both identifiers on the edge. If the interaction is undirected, an empty list will be returned.

sources_reverse(resources=False, evidences=False, resource_names=False, sources=False)§

Retrieves the list of sources for the b_a direction.

Returns:: (set) – Contains the names of the sources supporting the b_a directionality of the edge.

sources_straight(resources=False, evidences=False, resource_names=False, sources=False)§

Retrieves the list of resources for the a_b direction.

Returns:: (set) – Contains the names of the sources supporting the a_b directionality of the edge.

sources_undirected(resources=False, evidences=False, resource_names=False, sources=False)§

Retrieves the list of resources without directed information.

Returns:: (set) – Contains the names of the sources supporting the edge presence but without specific directionality information.

src(undirected: bool = False, resources=None, **kwargs)§

Returns the name(s) of the source node(s) for each existing direction on the interaction.

Args

undirected:: Optional, False by default.

Returns

src_by_resource(resource)[source]§

Returns the name(s) of the source node(s) for each existing direction on the interaction for a specific resource.

Parameters:: resource (str) – Name of the resource according to which the information is to be retrieved.
Returns:: (list) – Contains the name(s) for the source node(s) according to the specified resource. This means if the interaction is bidirectional, the list will contain both identifiers on the edge. If the specified source is not found or invalid, an empty list will be returned.

target(undirected: bool = False, resources=None, **kwargs)[source]§

Returns the name(s) of the target node(s) for each existing direction on the interaction.

Args

undirected:: Optional, False by default.

Returns

(list) – Contains the name(s) for the target node(s). This means if the interaction is bidirectional, the list will contain both identifiers on the edge. If the interaction is undirected, an empty list will be returned.

tgt(undirected: bool = False, resources=None, **kwargs)§

Returns the name(s) of the target node(s) for each existing direction on the interaction.

Args

undirected:: Optional, False by default.

Returns

tgt_by_resource(resource)[source]§

Returns the name(s) of the target node(s) for each existing direction on the interaction for a specific resource.

Parameters:: resource (str) – Name of the resource according to which the information is to be retrieved.
Returns:: (list) – Contains the name(s) for the target node(s) according to the specified resource. This means if the interaction is bidirectional, the list will contain both identifiers on the edge. If the specified source is not found or invalid, an empty list will be returned.

translate(ids, new_attrs=None)[source]§

Translates the node names/identifiers according to the dictionary ids. Also is able to change attributes like id_type, taxon and entity_type.

Parameters:

ids (dict) – Dictionary containing (at least) the current names of the nodes as keys and their translation as values.
new_attrs (dict) – Dictionary with new IDs as keys and their dicts of their new attributes as values. For any attribute not provided here the attributes from the original instance will be used. E.g. you can provide `{‘1956’: {‘id_type’: ‘entrez’}}’ if the new ID type for protein EGFR is Entrez Gene ID.

Returns:

(pypath.main.Direction) – The copy of current edge object with translated node names.

unset_dir(direction, only_sign=False, resource=None, interaction_type=None, via=False, source=None)§

Removes directionality and/or source information of the specified direction. Modifies attribute dirs and sources.

Parameters:

direction (tuple) – Or [str] (if 'undirected') the pair of nodes specifying the directionality from which the information is to be removed.
resource (set) – Optional, None by default. If specified, determines which specific source(s) is(are) to be removed from sources attribute in the specified direction.

unset_direction(direction, only_sign=False, resource=None, interaction_type=None, via=False, source=None)[source]§

Removes directionality and/or source information of the specified direction. Modifies attribute dirs and sources.

Parameters:

direction (tuple) – Or [str] (if 'undirected') the pair of nodes specifying the directionality from which the information is to be removed.
resource (set) – Optional, None by default. If specified, determines which specific source(s) is(are) to be removed from sources attribute in the specified direction.

unset_interaction_type(interaction_type)[source]§: Removes all evidences with a certain interaction_type.

unset_sign(direction, sign, resource=None, interaction_type=None, via=False, source=None)[source]§

Removes sign and/or source information of the specified direction and sign. Modifies attribute positive and positive_sources or negative and negative_sources (or positive_attributes/negative_sources only if source=True).

Parameters:

direction (tuple) – The pair of nodes specifying the directionality from which the information is to be removed.
sign (str) – Sign from which the information is to be removed. Must be either 'positive' or 'negative'.
source (set) – Optional, None by default. If specified, determines which source(s) is(are) to be removed from the sources in the specified direction and sign.

update_attrs(attrs=None, **kwargs)§

Updates the attributes stored here. The attributes with identical keys are merged using the pypath.share.common.combine_attrs() function.

The new attributes can be provided three ways: an object with an attribute called attrs; a dictionary of attributes; or the attributes as keyword arguments.

which_directions(resources=None, effect=None)[source]§

Returns the pair(s) of nodes for which there is information about their directionality.

Parameters:

effect (str) – Either positive or negative.
resources (str,set) – Limits the query to one or more resources. Optional.

Returns:

(tuple) – Tuple of tuples with pairs of nodes where the first element is the source and the second is the target entity, according to the given resources and limited to the effect.

which_dirs(resources=None, effect=None)§

Returns the pair(s) of nodes for which there is information about their directionality.

Parameters:

effect (str) – Either positive or negative.
resources (str,set) – Limits the query to one or more resources. Optional.

Returns:

(tuple) – Tuple of tuples with pairs of nodes where the first element is the source and the second is the target entity, according to the given resources and limited to the effect.

which_signs(resources=None, effect=None)[source]§

Returns the pair(s) of nodes for which there is information about their effect signs.

Parameters:

resources (str,set) – Limits the query to one or more resources. Optional.
effect (str) – Either positive or negative, limiting the query to positive or negative effects; for any other values effects of both signs will be returned.

Returns:

(tuple) – Tuple of tuples with pairs of nodes where the first element is a tuple of the source and the target entity, while the second element is the effect sign, according to the given resources. E.g. (((‘A’, ‘B’), ‘positive’),)