Knowledge Graph
Search, explore, and traverse 280K+ cancer biology entities and 4.75M relationships.
/entities/{entity_id}/entities/search/entities/{entity_id}/relationships+3 more endpoints
Programmatic access to a 280,000+-entity cancer knowledge graph with causal inference, drug-target analysis, and clinical interpretation. Built for developers, researchers, and AI agents.
280K+
entities
4.75M+
relationships
28
data sources
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No free biomedical API offers causal inference, counterfactual reasoning, or patient-level mutation interpretation. Galen does.
| Capability | Galen | PubChem | BioThings | Open Targets |
|---|---|---|---|---|
| Cancer knowledge graph | ||||
| Causal inference (do-calculus) | ||||
| Counterfactual reasoning | ||||
| Multi-mutation patient interpretation | ||||
| Drug bioactivity data | ||||
| Gene essentiality (CRISPR) | ||||
| Pearl Causal Hierarchy (L1/L2/L3) | ||||
| Clinical trial matching |
From entity search to causal inference to patient interpretation — everything connected through a unified knowledge graph.
Search, explore, and traverse 280K+ cancer biology entities and 4.75M relationships.
/entities/{entity_id}/entities/search/entities/{entity_id}/relationships+3 more endpoints
Query 28 integrated biomedical databases through a unified API.
/chembl/compound/{name}/depmap/gene/{gene}/gdsc/drug/{drug}+5 more endpoints
Simulate interventions, run do-calculus queries, and explore counterfactual scenarios.
/causal/intervention/causal/explain/causal/do-calculus+4 more endpoints
Predict drug responses, gene essentiality, and mutation effects with confidence scores.
/predictions/drug-response/predictions/essentiality/predictions/mutation-effect+1 more endpoints
Discover knowledge gaps and explore the frontier of cancer biology.
/hypotheses/frontier/hypotheses/gaps/{entity}Interpret multi-mutation profiles, find treatments, match clinical trials.
/patient/profile/patient/treatments/patient/resistance+2 more endpoints
Health checks, system statistics, and data source information.
/health/health/status/health/stats+1 more endpoints
Query the knowledge graph, simulate causal interventions, and explore downstream effects — all through simple REST calls.
import requests
API_KEY = "your_api_key"
BASE = "https://research.usegalen.com/api/v1"
# Find all EGFR relationships in the knowledge graph
resp = requests.get(
f"{BASE}/entities/EGFR/relationships",
headers={"X-API-Key": API_KEY},
params={"limit": 10}
)
relationships = resp.json()["relationships"]
# Simulate inhibiting EGFR — what happens downstream?
causal = requests.post(
f"{BASE}/causal/intervention",
headers={"X-API-Key": API_KEY},
json={
"target": "EGFR",
"intervention_type": "inhibit"
}
)
print(causal.json()["downstream_effects"])Start free. Scale when you need to. No surprise charges.
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