A knowledge graph for relational learning on biological data.
BioKG requires python3.7 or greater to run
git clone https://github.com/dsi-bdi/biokg.git
cd biokg
pip install -r requirements.txt
python run_all.py '<drugbank_username>' '<drugbank_password>'
After the script completes there should be a data folder in the biokg folder This data folder will have 4 folders
- sources which contains the sources used to compile BioKG
- preprocessed which contains the extracted data in preprocessed form
- output which contains the process data and benchmarks
- biokg which contains the final biokg data
There will also be 2 zip files similar to the files contained in the release
- biokg.zip which contains the compressed contents of the biokg folder
- benchmarks.zip which contains the compressed contents of the output/benchmarks folder
sudo docker build . -t dsi-bdi/biokg
sudo docker run --rm -v <data_path>:/biokg/data -e DB_USER='<drugbank_username>' -e DB_PASS='<drugbank_password>' dsi-bdi/biokg:latest
- where <data_path> is the fully qualified path to your data folder
The biokg is built using the following data sources.
Source Database | License Type | URL |
---|---|---|
UniProt | CC BY 4.0 | https://www.uniprot.org/help/license |
Drugbank | CC BY NC 4.0 | https://www.drugbank.ca/legal/terms_of_use |
KEGG | Custom | https://www.kegg.jp/kegg/legal.html |
Sider | CC BY-NC-SA | http://sideeffects.embl.de/about/ |
HPA | CC BY SA 3.0 | https://www.proteinatlas.org/about/licence |
Cellosaurus | CC BY 4.0 | https://web.expasy.org/cgi-bin/cellosaurus/faq#Q22 |
Reactome | CC0 | https://reactome.org/license |
CTD | Custom | http://ctdbase.org/about/legal.jsp |
Intact | Apache 2.0 | https://www.ebi.ac.uk/intact/downloads |
MedGen | Custom | https://www.nlm.nih.gov/databases/download/terms_and_conditions.html |
MESH | Custom | https://www.nlm.nih.gov/databases/download/terms_and_conditions.html |
InterPro | Custom | ftp://ftp.ebi.ac.uk/pub/databases/interpro/release_notes.txt |
SMPDB | Custom | https://smpdb.ca/about |
Hajazi20 | ||
The development of this module has been fully supported by the CLARIFY project that has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 875160.