biotender-max/query-reactome
Query Reactome for biological pathways and reactions. Use when user asks about signaling cascades, biological processes, pathway diagrams, or reaction details. Triggers on "reactome", "signaling cascade", "biological pathway", "pathway diagram", "reaction mechanism".
npx skills add https://github.com/BioTender-max/awesome-bio-agent-skills --skill query-reactome
Query the Reactome ContentService and AnalysisService APIs.
import requests
import json
CONTENT_URL = "https://reactome.org/ContentService"
ANALYSIS_URL = "https://reactome.org/AnalysisService"
# 1. Search pathways by keyword
def search_pathways(keyword, species="Homo sapiens"):
url = f"{CONTENT_URL}/search/query"
params = {"query": keyword, "species": species, "types": "Pathway", "cluster": True}
r = requests.get(url, params=params)
r.raise_for_status()
return r.json()
# 2. Get pathway details
def get_pathway(pathway_id):
url = f"{CONTENT_URL}/data/query/{pathway_id}"
r = requests.get(url, headers={"Accept": "application/json"})
r.raise_for_status()
return r.json()
# 3. Get genes/proteins in a pathway
def get_pathway_participants(pathway_id):
url = f"{CONTENT_URL}/data/participants/{pathway_id}"
r = requests.get(url, headers={"Accept": "application/json"})
r.raise_for_status()
return r.json()
# 4. Gene list pathway enrichment
def pathway_enrichment(gene_list):
url = f"{ANALYSIS_URL}/identifiers/projection"
genes_text = "\n".join(gene_list)
headers = {"Content-Type": "text/plain"}
r = requests.post(url, data=genes_text, headers=headers)
r.raise_for_status()
return r.json()
# 5. Look up a gene in Reactome
def query_gene(gene_symbol):
url = f"{CONTENT_URL}/data/query/{gene_symbol}"
r = requests.get(url, headers={"Accept": "application/json"})
r.raise_for_status()
return r.json()
# Example: DNA repair pathways
results = search_pathways("DNA repair")
entries = results.get("results", [])
for entry in entries[:5]:
for e in entry.get("entries", []):
print(f"{e.get('stId', 'N/A')}: {e.get('name', 'N/A')}")
# Pathway enrichment
enrichment = pathway_enrichment(["BRCA1", "BRCA2", "TP53", "ATM", "CHEK2"])
for p in enrichment.get("pathways", [])[:5]:
name = p.get("name", "N/A")
pval = p.get("entities", {}).get("pValue", "N/A")
found = p.get("entities", {}).get("found", 0)
print(f"{name} — p={pval:.2e}, {found} genes found")
R-HSA-73894R-HSA-109581R-HSA-1640170R-HSA-168256Take biotender-max/query-reactome from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.