ArticleScientific data2023
The OREGANO knowledge graph for computational drug repurposing.
Article in Scientific data, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Computer-Interpretable Domain Knowledge for Drug-Induced Acute Kidney Injury: a Knowledge Graph Approach.Scientific data · 2026Article
- AI and network biology for rational polypharmacology in signaling drug design: a review.NPJ precision oncology · 2026Review
- Generating explainable hypotheses for drug repurposing with graph neural networks.Scientific reports · 2026Article
- RNA-KG v2.0: an RNA-centered Knowledge Graph with Properties.NAR genomics and bioinformatics · 2026Article
- CellAwareGNN: Single-Cell Enhanced Knowledge Graph Foundation Model for Drug Indication Prediction.bioRxiv : the preprint server for biology · 2026Article
- Therapeutic monoclonal antibodies repurposing in oncology via IMGT/mAb-KG embeddings.BMC medical informatics and decision making · 2026Article
- An epidemiological knowledge graph extracted from the World Health Organization's Disease Outbreak News.Scientific data · 2025Article
- Drug repurposing for Alzheimer's disease and other neurodegenerative disorders.Nature communications · 2025Review
- A knowledge graph for crop diseases and pests in China.Scientific data · 2025Article
- Connecting electronic health records to a biomedical knowledge graph to link clinical phenotypes and molecular endotypes in atopic dermatitis.Scientific reports · 2025Article
- Knowledge Graphs for drug repurposing: a review of databases and methods.Briefings in bioinformatics · 2024Review
- Some Aspects and Convergence of Human and Veterinary Drug Repositioning.Molecules (Basel, Switzerland) · 2024Review
- An ontology-based knowledge graph for representing interactions involving RNA molecules.Scientific data · 2024Article
- Generative AI-based knowledge graphs for the illustration and development of mHealth self-management content.Frontiers in digital health · 2024Article
- Advancing drug-target interaction prediction: a comprehensive graph-based approach integrating knowledge graph embedding and ProtBert pretraining.BMC bioinformatics · 2023Article
- The OREGANO knowledge graph for computational drug repurposing.Scientific data · 2023Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Drug repositioning is a faster and more affordable solution than traditional drug discovery approaches. From this perspective, computational drug repositioning using knowledge graphs is a very promising direction. Knowledge graphs constructed from drug data and information can be used to generate hypotheses (molecule/drug - target links) through link prediction using machine learning algorithms. However, it remains rare to have a holistically constructed knowledge graph using the broadest possible features and drug characteristics, which is freely available to the community. The OREGANO knowledge graph aims at filling this gap. The purpose of this paper is to present the OREGANO knowledge graph, which includes natural compounds related data. The graph was developed from scratch by retrieving data directly from the knowledge sources to be integrated. We therefore designed the expected graph model and proposed a method for merging nodes between the different knowledge sources, and finally, the data were cleaned. The knowledge graph, as well as the source codes for the ETL process, are openly available on the GitHub of the OREGANO project ( https://gitub.u-bordeaux.fr/erias/oregano ).
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.