AttentionDTA: prediction of drug–target binding affinity using attention model.https://ieeexplore.ieee.org/abstract/document/8983125
This repository contains the source code and the data.
Dependencies:
- python 3.6
- tensorflow >=1.9
- numpy
- README.md: this file.
- tfrecord: The original data set and data set processing code are saved in this folder.
- davis_div.txt: Under the 5-fold cross-validation setting, there is a division of the training set and the test set of the davis dataset.
- kiba_div.txt: Under the 5-fold cross-validation setting, there is a division of the training set and the test set of the kiba dataset.
- davis_str_all.txt
- kiba_str_all.txt
- dataset.py: create data in tfrecord format according to (kiba/davis)_div.txt
- DTA_train.py: train a AttentionDTA model.
- DTA_model.py: AttentionDTA model architecture
- DTA_test.py: test trained models
python dataset.py
python DTA_train.py To train a model using training data.
python DTA_test.py