KGNN
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Source Code for IJCAI'20 "KGNN: Knowledge Graph Neural Network for Drug-Drug Interaction Prediction"
Knowledge Graph Neural Network
This is our implementation for the paper
Xuan Lin, Zhe Quan, Zhi-Jie Wang, Tengfei Ma and Xiangxiang Zeng. KGNN: Knowledge Graph Neural Network for Drug-Drug Interaction Prediction. IJCAI' 20 accepted.
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Requirement
To run the code, you need the following dependencies:
- Python == 3.6.6
- Keras == 2.3.0
- Tensorflow == 1.13.1
- scikit-learn == 0.22
Installation
You can create a virtual environment using conda.
conda create -n kgnn python=3.6.6
source activate kgnn
git clone https://github.com/xzenglab/KGNN.git
cd KGNN
pip install -r requirement.txt
Dataset
We just provide the preprocessed KG from KEGG-drug dataset owing to the size limited. And you can directly download the original DrugBank dataset (V5.1.4). Note that the construction of KG please refer to Bio2RDF tool in detail.
Usage
python run.py
Citation
@inproceedings{ijcai2020-380,
title = {KGNN: Knowledge Graph Neural Network for Drug-Drug Interaction Prediction},
author = {Lin, Xuan and Quan, Zhe and Wang, Zhi-Jie and Ma, Tengfei and Zeng, Xiangxiang},
booktitle = {Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, {IJCAI-20}},
publisher = {International Joint Conferences on Artificial Intelligence Organization},
editor = {Christian Bessiere},
pages = {2739--2745},
year = {2020},
month = {7},
note = {Main track},
doi = {10.24963/ijcai.2020/380},
url = {https://doi.org/10.24963/ijcai.2020/380},
}
For any clarification, comments, or suggestions please create an issue or contact Jacklin.