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Code and Datasets for "Predicting Drug-Disease Associations through Layer Attention Graph Convolutional Networks"

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LAGCN

Code and Datasets for "Predicting Drug-Disease Associations through Layer Attention Graph Convolutional Networks" https://doi.org/10.1093/bib/bbaa243

Datasets

  • data/drug_dis.csv is the drug_disease association matrix, which contain 18416 associations between 269 drugs and 598 diseases.

  • data/drug_sim.csv is the drug similarity matrix of 269 diseases,which is calculated based on drug target features.

  • data/dis_sim.csv is the disease similarity matrix of 598 diseases,which is calculated based on disease mesh descriptors.

Code

Environment Requirement

The code has been tested running under Python 3.6.8. The required packages are as follows:

  • numpy == 1.15.4
  • scipy == 1.1.0
  • tensorflow == 1.12.0

Usage

git clone https://github.com/storyandwine/LAGCN.git
cd LAGCN/code
python main.py

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Code and Datasets for "Predicting Drug-Disease Associations through Layer Attention Graph Convolutional Networks"

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