Official code repository for our paper Deep Graph Networks for Drug Repurposing with Multi-Protein Targets.
If you find our work useful for your research, please consider citing the following paper:
@article{gravina2023DrugRep,
author = {Bacciu, Davide and Errica, Federico and Gravina, Alessio and Madeddu, Lorenzo and Podda, Marco and Stilo, Giovanni},
title = {Deep Graph Networks for Drug Repurposing with Multi-Protein Targets},
journal = {IEEE Transactions on Emerging Topics in Computing},
year = {2023},
volume={}
number={},
pages={1-14},
doi={10.1109/TETC.2023.3238963}
}
We provide a script to install the environment. You will need the conda package manager, which can be installed from here.
To install the required packages (tested on a linux terminal):
-
clone the repository
git clone https://github.com/gravins/covid19-drug-repurposing-with-DGNs.git
-
cd into the cloned directory
cd covid19-drug-repurposing-with-DGNs
-
run the install script
./requirements/install_cpu.sh
The script will create a virtual environment named covid-cpu
, with all the required packages needed to run our code.
The zipped dataset folder can be downloaded from here.
Note: To run the experiment is fundamental to define the task and model in the file run.sh or run_cluster.sh files.
-
if you run the experiment on a standard machine:
./run.sh
-
if you run the experiment on cluster managed by slurm:
./run_cluster.sh
-
if you want to run the GraphDTA or DeepDTA baseline then
cd DeepPurpose_baselines
python3 -u main.py
- For more details launch
python3 main.py --help
If you get errors like /lib64/libstdc++.so.6: version 'GLIBCXX_3.4.21' not found
:
conda install -c conda-forge c-compiler cxx-compiler
echo $LD_LIBRARY_PATH
should contain:[path to your anaconda or miniconda folder name]/lib