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AMDGT: attention aware multi-modal learning using dual graph transformer for drug-disease associations prediction

Requirements:

  • python 3.9.13
  • cudatoolkit 11.3.1
  • pytorch 1.10.0
  • dgl 0.9.0
  • networkx 2.8.4
  • numpy 1.23.1
  • scikit-learn 0.24.2

Data:

The data files needed to run the model, which contain C-dataset and F-dataset.

  • Drug_mol2vec: The mol2vec embeddings for drugs to construct the association network
  • DrugFingerprint, DrugGIP: The similarity measurements of drugs to construct the similarity network
  • DiseaseFeature: The disease embeddings to construct the association network
  • DiseasePS, DiseaseGIP: The similarity measurements of diseases to construct the similarity network
  • Protein_ESM: The ESM-2 embeddings for proteins to construct the association network
  • DrugDiseaseAssociationNumber: The known drug disease associations
  • DrugProteinAssociationNumber: The known drug protein associations
  • ProteinDiseaseAssociationNumber: The known disease protein associations

Code:

  • data_preprocess.py: Methods of data processing
  • metric.py: Metrics calculation
  • train_DDA.py: Train the model

Usage:

Execute python train_DDA.py

amdgt's People

Contributors

jk-liu7 avatar

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