This is the official implementation for the paper "MMPG: MoE-based Adaptive Multi-Perspective Graph Fusion for Protein Representation Learning".
- Python 3.10.14
- bio==1.7.1
- torch-2.1.0+cu121 -Torch-geometric 2.6.0
We use the four datasets, which can be found at:
https://github.com/DeepGraphLearning/torchdrug
https://github.com/divelab/DIG
To preprocess the data, please use the scripts from dataset fold.
python train.py
The evaluation can be automatically implemented after training. You can also change the train.py to implement it individually.
If you find our work useful, please consider citing it as follows:
@article{wang2026mmpg,
title={MMPG: MoE-based Adaptive Multi-Perspective Graph Fusion for Protein Representation Learning},
volume={40},
url={https://ojs.aaai.org/index.php/AAAI/article/view/37096},
DOI={10.1609/aaai.v40i2.37096},
journal={Proceedings of the AAAI Conference on Artificial Intelligence},
author={Wang, Yusong and Shen, Jialun and Wu, Zhihao and Xu, Yicheng and Tan, Shiyin and Xu, Mingkun and Wang, Changshuo and Song, Zixing and Tiwari, Prayag},
year={2026},
month={Mar.},
pages={1240-1248}
}