Oliver's mTOR Atlas
# Oliver's mTOR Atlas
A curated, evidence-graded database of mTOR pathway research in which every claim carries its source, the conditions it was measured under, and the point where it stops holding. Studies are labelled by the kind of study behind them - from synthesis of human data down to mechanistic and in-vitro work - and traced back to their primary source, alongside a knowledge-graph view of genes, diseases, and interventions and a layer of open questions naming what the evidence does not yet resolve.
**Live site:** https://mtor-atlas.org
[](https://doi.org/10.5281/zenodo.22059963)
## What's inside
- 400+ hand-curated primary studies on the mTOR signaling pathway (mTORC1/mTORC2, autophagy, rapamycin and related interventions), each labelled by the kind of study behind it and linked back to its DOI/PubMed record.
- A knowledge-graph view connecting genes, diseases, and interventions.
- An "open questions" layer - evidence gaps identified across the corpus, each paired with a proposed testable experiment.
- A citation-grounded research assistant that answers pathway questions using only the indexed corpus, with links back to source studies.
## Evidence grading
Studies are hand-selected from PubMed / Europe PMC and labelled by **study design**, not by quality, importance, or citation count:
- **S** - synthesis of human data (systematic review / meta-analysis)
- **H** - human study (clinical trial or observational)
- **A** - animal model
- **M** - molecular / in-vitro (mechanistic)
- **R** - review
These codes ran A-D until September 2026. They were renamed because a lettered ladder reads as a quality grade, which it never was, and because the old bottom tier merged primary mechanistic work with narrative reviews - two different kinds of claim. The change was prompted by an external critique from a researcher in the field; the underlying data was not re-graded, only the labels shown to readers.
A mechanistic paper is not "worse" than a trial. The code says what kind of claim a study can support, not how good it is.
## About this project
Built and maintained independently by Oliver, a high-school student, together with his father Petr. Not affiliated with any lab, company, or institution. Feedback on the evidence grading, missing studies, or anything that looks wrong is very welcome - please open an issue. See [CONTRIBUTING.md](CONTRIBUTING.md).
## Programmatic access
- **JSON API** (read-only, no key): https://mtor-atlas.org/api/ - studies with evidence codes, entities, signed pathway relations with supporting and conflicting studies, open questions. OpenAPI 3.1: https://mtor-atlas.org/api/openapi.json
- **MCP server** for AI assistants: source and install instructions in [`mcp/`](mcp/).
## Citing this dataset
If you use this dataset, please cite it via its Zenodo record: https://doi.org/10.5281/zenodo.22059963
A single page with all identifiers, registrations (bio.tools, FAIRsharing, GitHub, ORCID) and a ready-to-use citation is at https://mtor-atlas.org/data/.
## License
This repository is dual-licensed, because it contains two different kinds of thing:
- **Curated content and data** - the study records, evidence grades, curated prose, gap hypotheses, and everything under `atlas_data/` and the generated pages - are licensed under **CC BY 4.0** (see [LICENSE](LICENSE)): https://creativecommons.org/licenses/by/4.0/
- **Source code** - the Python generators, validation and verification scripts, and site JavaScript - is licensed under the **MIT License** (see [LICENSE-CODE](LICENSE-CODE)).
If you reuse the data, attribute it. If you reuse the code, MIT terms apply.
TDQS
Scored across 11 tools
Most tools target distinct resources (studies, entities, relations, questions) with clear get_/search_ pairs. However, evidence_between overlaps with find_relations (both return curated relations, the former just a special case for a two-entity pair), and find_contradictions overlaps with find_relations' contested-status filter. Descriptions help but an agent could still misselect among the relation-oriented tools.
The set is predominantly snake_case verb_noun (search_studies, get_study, find_relations, list_questions), which is readable and predictable. The main deviation is the inconsistent use of search_ vs find_ for essentially the same lookup semantics, plus the noun-only atlas_about.
11 tools is well-scoped for a read-only curated atlas, with each tool mapping to a distinct resource or query pattern. No tool feels redundant or trivially thin.
The surface covers the full read lifecycle for the domain: metadata (atlas_about), search+get for studies, entities, relations and questions, plus specialized views for evidence-between and contradictions. As a curated read-only dataset, no create/update/delete is needed, so coverage is complete.