The code for "Heterogeneous Causal Metapath Graph Neural Network for Gene-Microbe-Disease Association Prediction (IJCAI 2024)".

The repository is organized as follows:

• Data/ contains the datasets used in the paper;
• Utils/ contains the processing functions and tools;
• data_process.py contains reading the initial features and generate train and test samples;
• train.py contains the training and testing code of 5-fold CV and independent test experiments on datasets;
• model.py contains the components of the model.
• main.py main program of the repository;

• python == 3.8.13
• pytorch == 1.9.0
• numpy == 1.21.0
• dgl == 0.6.0post1
• dglke == 0.1.2
• scikit-learn == 1.1.1

Here we provide a example of using MCHNN , execute the following command:

python main.py --loss_gamma 0.7 --lr 0.005