Identifying Cellular Relations
- Python 3
- MySQL server or SQLite
First install requirements
pip install -r requirements.txt
git clone https://github.com/lasigeBioTM/MER.git
Change config/database.config accordingly
Download cl.owl from https://bioportal.bioontology.org/ontologies/CL
Download cytokine registry from http://www.immport.org/immport-open/public/reference/cytokineRegistry and convert it to csv Move both files to data/
python database_schema.py
python generate_cell_names.py
python generate_cytokine_names_entrez.py
Copy data/cell.txt and data/cytokine.txt to MER/data/ and run ./produce_data_files cell
and ./produce_data_files cytokine
Change config/immuno.config or create a new file according to your specifications
python generate_corpus.py -c config/immuno.config
Create directories temp/ and results/
python run_ds -c config/train_immuno.config
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A. Lamurias, J. Ferreira, L. Clarke, and F. Couto, “Generating a tolerogenic cell therapy knowledge graph from literature,” Frontiers in Immunology, vol. 8, no. 1656, pp. 1--23, 2017 (https://doi.org/10.3389/fimmu.2017.01656)
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A. Lamurias, L. Clarke, and F. Couto, “Extracting microRNA-gene relations from biomedical literature using distant supervision,” PLoS ONE, vol. 12, no. 3, pp. 1--20, 2017 (https://doi.org/10.1371/journal.pone.0171929)