Olivers mTOR Atlas

Oliver's mTOR Atlas curates and evidence-grades mTOR pathway research, linking peer-reviewed primary studies to a knowledge graph of genes, diseases, and interventions with explicit study-type labels, source attribution, experimental conditions, validity boundaries, and documented knowledge gaps.

Key Features:

• Evidence-graded curation: Every claim carries its source, the conditions it was measured under, and the point where its validity ends.
• Study-type labelling: Primary studies are labelled by kind of study: S = synthesis of human data, H = human study, A = animal model, M = molecular/in vitro, R = review.
• Knowledge graph integration: Studies are linked to genes, diseases, and interventions.
• Knowledge gaps and hypotheses: The database includes named knowledge gaps and testable hypotheses documenting what the literature has tested and failed to show, and what it has not tested at all.
• Data access: Data are available through a read-only JSON API (OpenAPI 3.1) and an MCP server for AI assistants.

Scientific Applications:

• mTOR pathway research: Researchers can query evidence-graded findings on mTOR biology across more than 400 primary studies.
• Evidence synthesis: Users can assess claims by the system in which findings were established (human, animal, molecular, or synthesis of human data) rather than by arbitrary ranking.
• Hypothesis generation: The documented knowledge gaps and untested hypotheses support identification of new research directions.
• Knowledge graph exploration: Users can navigate relationships between genes, drugs, diseases, pathways, and outcomes in mTOR biology.

Methodology:

Hand-curation of primary studies with assignment of study-type codes and linking to a knowledge graph of genes, diseases, and interventions; data are made available via a read-only JSON API (OpenAPI 3.1) and an MCP server for AI assistants.