Reactome Interactors Tools#
Configuration File: reactome_interactors_tools.json
Tool Type: Local
Tools Count: 3
This page contains all tools defined in the reactome_interactors_tools.json configuration file.
Available Tools#
ReactomeInteractors_get_entity_pathways (Type: ReactomeInteractorsTool)#
Find Reactome biological pathways that contain a specific molecular entity. Returns pathway stabl…
ReactomeInteractors_get_entity_pathways tool specification
Tool Information:
Name:
ReactomeInteractors_get_entity_pathwaysType:
ReactomeInteractorsToolDescription: Find Reactome biological pathways that contain a specific molecular entity. Returns pathway stable IDs, names, and whether they are disease-associated. Use Reactome stable IDs (e.g., R-HSA-199420 for PTEN) obtained from ReactomeInteractors_search_entity. Example: R-HSA-199420 (PTEN) participates in 10 pathways including PI3K/AKT signaling, PTEN regulation, and TCR signaling.
Parameters:
entity_id(string) (required) Reactome stable identifier for the entity. Use ReactomeInteractors_search_entity to find IDs. Examples: ‘R-HSA-199420’ (PTEN), ‘R-HSA-69541’ (TP53 tetramer), ‘R-HSA-8869337’ (TP53).species([‘integer’, ‘null’]) (optional) NCBI taxonomy ID for species filter (default: 9606 for human). Examples: 9606 (human), 10090 (mouse).
Example Usage:
query = {
"name": "ReactomeInteractors_get_entity_pathways",
"arguments": {
"entity_id": "example_value"
}
}
result = tu.run(query)
ReactomeInteractors_get_protein_interactors (Type: ReactomeInteractorsTool)#
Get protein-protein interaction partners from Reactome’s IntAct-derived data. Returns the authori…
ReactomeInteractors_get_protein_interactors tool specification
Tool Information:
Name:
ReactomeInteractors_get_protein_interactorsType:
ReactomeInteractorsToolDescription: Get protein-protein interaction partners from Reactome’s IntAct-derived data. Returns the authoritative total plus a pageable set of interactors; when has_more is true pass next_page as page with the same accession and page_size. Interactions include confidence scores and evidence counts.
Parameters:
accession(string) (required) UniProt accession number for the query protein. Examples: ‘P04637’ (TP53), ‘Q04206’ (NF-kB p65), ‘P00533’ (EGFR), ‘P38398’ (BRCA1).page_size([‘integer’, ‘null’]) (optional) Maximum number of interactors to return on this page (default: 20). Not capped - pass a value >= total_interactors (e.g. 300 for P04637) to retrieve every interactor in one call.page(integer) (optional) One-based Reactome interactor page. Continue with next_page while has_more is true.
Example Usage:
query = {
"name": "ReactomeInteractors_get_protein_interactors",
"arguments": {
"accession": "example_value"
}
}
result = tu.run(query)
ReactomeInteractors_search_entity (Type: ReactomeInteractorsTool)#
Search and page through Reactome biological entities by name or identifier. Reactome groups resul…
ReactomeInteractors_search_entity tool specification
Tool Information:
Name:
ReactomeInteractors_search_entityType:
ReactomeInteractorsToolDescription: Search and page through Reactome biological entities by name or identifier. Reactome groups results by entity type and applies limit/offset independently inside every group: limit=2 can therefore return up to two Proteins, two Complexes, two Pathways, etc., not two records globally. Metadata reports aggregate numberOfMatches, actual returned count, per-group totals, rows_per_group, and next_offset.
Parameters:
query(string) (required) Search query - gene name, protein name, pathway name, or Reactome ID. Examples: ‘TP53’, ‘BRCA1’, ‘apoptosis’, ‘insulin signaling’, ‘cell cycle’.species([‘string’, ‘null’]) (optional) Species name filter (default: ‘Homo sapiens’). Examples: ‘Homo sapiens’, ‘Mus musculus’, ‘Rattus norvegicus’.types([‘string’, ‘null’]) (optional) Entity type filter. Options: ‘Protein’, ‘Complex’, ‘Reaction’, ‘Pathway’, ‘SmallMolecule’. If null, returns all types.limit(integer) (optional) Rows to request per Reactome result-type group, not a global response maximum.offset(integer) (optional) Zero-based start row applied independently within every result-type group. Continue with metadata.next_offset.
Example Usage:
query = {
"name": "ReactomeInteractors_search_entity",
"arguments": {
"query": "example_value"
}
}
result = tu.run(query)