Drug Repurposing Datasets for Collaborative Filtering Methods

This repository is a part of the EU-funded RECeSS project (#101102016), and hosts the notebooks and code files which helped to build the following novel drug repurposing datasets:

• TRANSCRIPT dataset

• PREDICT dataset

The latest versions (v2.0.0 and v2.0.1 of May 29th, 2023) of those datasets correspond to the current notebooks in folder notebooks/. The notebooks corresponding to the v1.0.0 and v1.0.1 (December 28th, 2022) are hosted in folder notebooks/v1.0.0/. To get more details about the datasets themselves, please refer to the corresponding Zenodo pages.

Running the notebooks

Global variables

Update to your liking the following file paths_global.py. The corresponding files and how to obtain them are detailed in notebooks/FEATURELESS_dataset.ipynb.

Environment

In order to run the notebooks:

conda create -n drug_repurposing python=3.8.5 -y
conda activate drug_repurposing
python3 -m pip install -r requirements.txt
python3 -m pip install notebook>=6.5.4 markupsafe==2.0.1 ## packages for Jupyter notebook
conda deactivate
conda activate drug_repurposing
cd notebooks/ && jupyter notebook

Licence

These datasets and code are under an OSI-approved MIT license. Note that the final matrices for PREDICT are not available, due to the usage rules of the DrugBank dataset. However, one can run the corresponding notebook PREDICT_dataset.ipynb in order to get the final matrices. A partial dataset is downloadable on Zenodo.

Citation

Clémence Réda. (2023). 
Jupyter Notebooks for building drug repurposing datasets in collaborative filtering (v2.0.0). 
Zenodo. https://doi.org/10.5281/zenodo.8014774

Community guidelines with respect to contributions, issue reporting, and support

Pull requests and issue flagging are welcome, and can be made through the GitHub interface. Support can be provided by reaching out to recess-project[at]proton.me.