RNA-KG

RNA-KG is an ontology-based knowledge graph which encompasses biological knowledge about RNA molecules gathered from more than 60 public data sources, integrating functional relationships with genes, proteins, and chemicals and ontologically grounded biomedical concepts. RNA-KG is constantly maintained and updated with new experimental data. RNA-KG releases are updated on this webpage. More details can be found in our paper: https://www.nature.com/articles/s41597-024-03673-7.

Public SPARQL endpoint is available and maintained at the following link: https://blazegraph-RNA-KG.anacleto.di.unimi.it.
RNA-KG in N-Triples format and data+code for reproducing experiments are available at https://zenodo.org/doi/10.5281/zenodo.10078876.
Public Neo4j endpoint (⚠️experimental⚠️) is available and maintained at the following link: https://neo4j.anacleto.di.unimi.it (usr: anacleto; pwd: anacleto).

RNA-KG can be built from scratch by following the tutorials on the GitHub page (specifically, https://github.com/AnacletoLAB/RNA-KG/tree/main/notebooks contains Python notebook to build RNA-KG current release).

Here, we provide examples and tutorials on how to query RNA-KG and extract relevant subgraphs of interest, generate from scratch new RNA-KG views by means of the PheKnowLator ecosystem, and how to import KGs in the GRAPE library to infer new knowledge from RNA-KG using different kinds of embedding. While querying RNA-KG using SPARQL is straightforward and takes a few seconds to extract an RNA-KG subgraph of interest, using PheKnowLator for generating a new view ensures to obtain a fully-connected subgraph of RNA-KG.

At the following link https://rna-kg.anacleto.di.unimi.it/views we provide views already generated by our team, whose specification is reported for each view in a README.txt file. These views are thought to be used in combination with graph-oriented ML techniques for edge and node type labeling and heterogeneous/homogeneous link predictions tasks. For each view we also provide the correspondent metagraph (in pdf and xlsx formats) and two pickle dictionaries files for nodes and edges to facilitate the import in the GRAPE environment.

Finally, at the following link https://rna-kg.anacleto.di.unimi.it/nodes we provide tabular files for each relationship between entities within RNA-KG. These files can be used for obtaining RNA-KG subgraphs that deal with partial subsets of node types and for importing RNA-KG in graph-oriented ML tools/environments different from GRAPE.

Don't hesitate to contact us, especially if you believe a new data source should be integrated into RNA-KG. To get in touch with us, please create an issue or send us an email 📩.

Citing RNA-KG

Please cite the following paper if RNA-KG was useful for your research:

@article{Cavalleri2024rnakg,
    title="An ontology-based knowledge graph for representing interactions involving RNA molecules",
    author="Emanuele Cavalleri and Alberto Cabri and Mauricio Soto-Gomez and Sara Bonfitto and Paolo Perlasca and Jessica Gliozzo and Tiffany J. Callahan and Justin Reese and Peter N Robinson and Elena Casiraghi and Giorgio Valentini and Marco Mesiti",
    year="2024",
    journal="Sci. Data",
    publisher="Springer Science and Business Media LLC",
    volume=11,
    number=1,
    pages="906",
    month=aug,
    year=2024,
    copyright="https://creativecommons.org/licenses/by-nc-nd/4.0",
    language="en"
}