--- license: other license_name: mixed-cc-by-4.0-and-cc0 license_link: https://reactome.org/license language: - en tags: - knowledge-graph - graph-database - cypher - biology - bioinformatics - pathways - proteomics - gene-ontology pretty_name: "Pathways Knowledge Graph (PARTIAL BUILD — known gaps)" size_categories: - 100K Contains data from **Reactome** (CC BY 4.0), **STRING v12.0** (CC BY 4.0), the > **Gene Ontology** (CC BY 4.0) and **UniProt** (CC BY 4.0). **WikiPathways** content is > released under **CC0**. None of these projects endorses this dataset or any analysis > derived from it. STRING additionally asks that you *"inform users of any changes or additions that you might have made to the data"* — this build applies a confidence threshold of 700 and maps ENSP identifiers to UniProt accessions. The Gene Ontology asks that a release be cited; this build used the `current` release as of 2026-08-29 rather than a pinned dated release (see *Source substitutions*). ### ⚠️ UniProt rights caveat UniProt's licence page carries a limitation that must travel with the data: > *"We cannot provide unrestricted permission regarding the use of the data, as some data may > be covered by patents or other rights."* CC BY 4.0 covers UniProt's own copyrightable content; it does not clear third-party patent or other rights that may attach to particular records. Satisfy yourself of this before commercial use of the UniProt-derived layer (`Protein`, `Gene`, `Disease`, `Drug` nodes). ### Repository licence is separate The [pathways-kg repository](https://github.com/samyama-ai/pathways-kg) code is **Apache-2.0**. That covers the loader and schema **only**. It does not govern the data in this dataset, which is bound by the five upstream licences above. `license: other` is used here because no single SPDX tag expresses "four CC BY 4.0 sources plus one CC0 source". **KEGG is deliberately absent.** The repository's design notes record that *"KEGG has restrictive licensing (no bulk download, no redistribution). We use open alternatives that collectively exceed KEGG's coverage."* That was a licence decision made at design time. ## Source substitutions Two of the five pinned source URLs in the repository are **dead**, so newer releases were substituted. This is part of why counts differ from the documented figures: | Source | Repository pins | 404s? | Used here | |--------|-----------------|-------|-----------| | WikiPathways | `wikipathways-20240310-gmt-Homo_sapiens.gmt` | **yes** | `wikipathways-20260810-gmt-Homo_sapiens.gmt` | | Gene Ontology | `release.geneontology.org/2024-06-17/ontology/go.json.gz` | **yes** | `current.geneontology.org/ontology/go.json` | Both substitutions *increase* node counts relative to the pinned versions. Neither can account for missing edges. ## Contents ### `nodes/` | File | Rows | |------|-----:| | `protein.csv` | 46,122 | | `goterm.csv` | 38,092 | | `gene.csv` | 19,086 | | `complex.csv` | 16,169 | | `drug.csv` | 8,486 | | `disease.csv` | 6,901 | | `pathway.csv` | 3,869 | `Pathway` = 2,883 Reactome + 986 WikiPathways. ### `edges/` | File | Rows | Connects | Status | |------|-----:|----------|--------| | `annotated_with.csv` | 232,365 | Protein → GOTerm | ✅ matches loader report | | `interacts_with.csv` | 227,971 | Protein → Protein | ✅ matches loader report | | `is_a.csv` | 57,456 | GOTerm → GOTerm | ✅ | | `targets.csv` | 32,793 | Drug → Protein | ✅ | | `encodes.csv` | 19,152 | Gene → Protein | ✅ | | `regulates.csv` | 8,190 | GOTerm → GOTerm | ✅ | | `associated_with.csv` | 7,302 | Protein → Disease | ✅ | | `part_of.csv` | 7,058 | GOTerm → GOTerm | ✅ | | `participates_in.csv` | **3,423** | Protein → Pathway | ⚠️ **loader reported 143,723** | | `child_of.csv` | 2,899 | Pathway → Pathway | ✅ | | `component_of.csv` | 2,713 | Protein → Complex | ⚠️ leaves 97% of complexes isolated | ## Usage ```python from datasets import load_dataset proteins = load_dataset("VaidhyaMegha/pathways-kg", "protein") ``` **Given the gaps above**, the layers worth using in this build are protein–protein interaction (STRING) and protein–GO annotation: ```cypher // Sound: STRING interaction neighbourhood MATCH (p:Protein {name: $gene})-[:INTERACTS_WITH]-(q:Protein) RETURN q.name LIMIT 25 // Sound: GO annotation with ontology closure MATCH (p:Protein)-[:ANNOTATED_WITH]->(t:GOTerm)-[:IS_A*1..3]->(a:GOTerm) WHERE a.name = $term RETURN DISTINCT p.name // NOT SOUND in this build — pathway membership is 2% populated // MATCH (p:Protein)-[:PARTICIPATES_IN]->(pw:Pathway) ... ``` ## Other limitations - **GO annotation coverage.** 906,445 annotations were parsed; **232,365 loaded**, with **105,433 skipped for having no matching protein**. Absence of an annotation here does not mean absence upstream. - **STRING is thresholded at confidence 700** — medium-to-high confidence only. Lower-scored interactions are excluded by design. - **Human only** (NCBI taxon 9606). - Point-in-time build of live sources; see the retrieval dates above. **Not clinical or diagnostic advice.** ## Citation ``` Pathways Knowledge Graph — PARTIAL BUILD (138,725 nodes, 601,322 edges). Built with Samyama Graph. https://huggingface.co/datasets/VaidhyaMegha/pathways-kg Loader: https://github.com/samyama-ai/pathways-kg Sources: Reactome (CC BY 4.0); STRING v12.0 (CC BY 4.0); Gene Ontology (CC BY 4.0); WikiPathways (CC0); UniProt (CC BY 4.0). All retrieved 2026-08-29. NOTE: partial build with known gaps — see the dataset card. Not a v1.0 release. ```