Trustworthy target identification: knowledge graphs, provenance, and grounding - what we actually know
09 Sept 2026
Target Identification
- Integrating internal vs external evidence: where do knowledge graphs and shared ontologies solve target-data harmonization, and where do they just move the problem?
- Attaching provenance and confidence to every target-supporting fact. How do we make model outputs auditable, not just plausible.
- Does grounding predictive models in structured, semantic knowledge meaningfully improve target relevance or just make it look more credible?
- Once entities are resolved across literature, omics, and clinical data, what separates true disease drivers from well-connected noise?
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