Bio-KGvec2go: Serving up-to-date dynamic biomedical knowledge graph embeddings
| Item Type: | Dataset |
|---|---|
| Title: | Bio-KGvec2go: Serving up-to-date dynamic biomedical knowledge graph embeddings |
| Date: | 2025 |
| Creator: |
Torres de Sousa, Rita Isabel  ORCID: 0000-0002-7241-8970
|
| Divisions: | School of Business Informatics and Mathematics > Data Science (Paulheim 2018-) |
| DDC Classification: |
004 Computer science, internet |
|---|---|
| Abstract: | Bio-KGvec2go (http://www.bio.kgvec2go.org/) is designed to generate and serve knowledge graph embeddings for widely used biomedical ontologies. Given the dynamic nature of these ontologies, Bio-KGvec2go also supports regular updates aligned with ontology version releases. By offering up-to-date embeddings with minimal computational effort required from users, Bio-KGvec2go facilitates efficient and timely biomedical research. (English) |
| External Identifier for Data: | https://doi.org/10.5281/zenodo.16636186 |
| URL: | https://madata.bib.uni-mannheim.de/991/ |
|---|---|
| Access (Controlled): | Only Metadata |
| License (Controlled): | Creative Commons: CC-BY | Attribution 4.0 (recommended) |
| Related Publication(s) in MADOC: | Ahmad, Hamid und Paulheim, Heiko und Sousa, Rita T. (2025), Bio-KGvec2go: Serving up-to-date dynamic biomedical knowledge graph embeddings |
Full text not available from this repository.
| Date Deposited: | 11 Jun 2026 14:39 |
|---|---|
| Last Modified: | 11 Jun 2026 14:39 |
You have found an error? Please let us know about your desired correction here: E-Mail
Actions (login required)
 |
View Item |
