Graph Auto Encoder and Convolutional neural network for Drug Synergy prediction
Title: Predicting Drug Synergy and Discovering New Drug Combinations Based on a Graph Autoencoder and Convolutional Neural Network
Interdisciplinary Sciences Computational Life Sciences 15(21)
DOI: 10.1007/s12539-023-00558-y
Code:
---------- * `GAECDS.py`: GAECDS model
* `GAECDS_cell_or_not.py`: GAECDS model with and without cell line data
* `GAECDS_cell_negative.py`: Training GAECDS model with different positive and negative sample ratios
* `GAECDS_param.py`: Hyperparameter adjustment
* `GAECDS_nocell_val.py`: Employ the model to predict novel drug combinations
Data:
data_5693: the data for train and test
data_1390: the data for new drug combinations prediction
machine_methods: the data for machine learning methods
Results:
The results of model training and the results of comparison