Source code for paper "M2GCN: Multi-Modal Graph Convolutional Network for Polypharmacy Side Effects Discovery"

The code has been tested under Python 3.8, with the following packages installed (along with their dependencies):

• torch >= 1.9.0
• pytorch-lightning >= 1.4.4
• torchmetrics >= 0.5.0
• torch-scatter >= 2.0.9
• torch-sparse >= 0.6.12
• numpy
• pandas
• tqdm
• yaml

Since git limits the size of a single file upload (<25M), we divide the datasets and the pre-trained models into multiple volumes. Please unzip the files in the directories dataandlightning_logs first.

cd ./data
sh do_unzip.sh
cd ../lightning_logs
sh do_unzip.sh

• /data: Store the dataset and prepared data.
• /dataloader: Codes of the dataloader.
• /models: Codes of the AGAT model , link-prediction task and simi-node-classification task .
• /utils: Codes for data prepareing and some other utils.
• /lightning_logs: Store the trained model parameters, setting files, checkpoints, logs and results.
• main.py: The main entrance of running.

train M2GCN by

python main.py

The default configuration file is setting/settings.yaml.

And if you want to adjust the hyperparameters of the model, you can modify it in .setting/settings.yaml, or create a similar configuration file, and specify --setting_path like this:

python main.py --setting_path yourpath.yaml

Checkpoints, logs, and results during training will be stored in the directory: ./lightning_logs/version_0

And you can run tensorboard --logdir lightning_logs/version_0 to monitor the training progress.

You can predict the interaction between drugs through the pre-trained model we provide.

Since git limits the size of a single file upload (<25M), we divide the pre-trained model into multiple volumes. Please unzip the files in the directory ./lightning_logs/pre-trained/checkpoints/ first.

Load the pre-trained model and predict the test dataset by:

python main.py --test --ckpt_path ./lightning_logs/pre-trained/checkpoints/pre-trained.ckpt

The result(auc,aupr) will be stored in the directory: ./lightning_logs/version_0

If you want to load your trained model to predict the test data set, you only need to change --ckpt_pathlike this:

python main.py --test --ckpt_path yourpath.ckpt

PS: Keep the configuration file unchanged during training and testing.