roysh / meta-mgnn

Few-Shot Graph Learning for Molecular Property Prediction

Few-shot Graph Learning for Molecular Property Prediction

Introduction

This is the source code and dataset for the following paper:

Few-shot Graph Learning for Molecular Property Prediction. In WWW 2021.

Contact Zhichun Guo ([email protected]), if you have any questions.

Datasets

The datasets uploaded can be downloaded to train our model directly.

The original datasets are downloaded from Data. We utilize Original_datasets/splitdata.py to split the datasets according to the molecular properties and save them in different files in the Original_datasets/[DatasetName]/new. Then run main.py, the datasets will be automatically preprocessed by loader.py and the preprocessed results will be saved in the Original_datasets/[DatasetName]/new/[PropertyNumber]/propcessed.

Usage

Installation

We used the following Python packages for the development by python 3.6.

- torch = 1.4.0
- torch-geometric = 1.6.1
- torch-scatter = 2.0.4
- torch-sparse = 0.6.1
- scikit-learn = 0.23.2
- tqdm = 4.50.0
- rdkit

Run code

Datasets and k (for k-shot) can be changed in the last line of main.py.

python main.py

Performance

The performance of meta-learning is not stable for some properties. We report two times results and the number of the iteration where we obtain the best results here for your reference.

Dataset	k	Iteration	Property	Results		k	Iteration	Property	Results
Sider	1	307/599	Si-T1	75.08/75.74		5	561/585	Si-T1	76.16/76.47
			Si-T2	69.44/69.34				Si-T2	68.90/69.77
			Si-T3	69.90/71.39				Si-T3	72.23/72.35
			Si-T4	71.78/73.60				Si-T4	74.40/74.51
			Si-T5	79.40/80.50				Si-T5	81.71/81.87
			Si-T6	71.59/72.35				Si-T6	74.90/73.34
			Ave.	72.87/73.82				Ave.	74.74/74.70
Tox21	1	1271/1415	SR-HS	73.72/73.90		5	1061/882	SR-HS	74.85/74.74
			SR-MMP	78.56/79.62				SR-MMP	80.25/80.27
			SR-p53	77.50/77.91				SR-p53	78.86/79.14
			Ave.	76.59/77.14				Ave.	77.99/78.05

Acknowledgements

The code is implemented based on Strategies for Pre-training Graph Neural Networks.

Reference

@inproceedings{guo2020metamgnn,
  title={Few-shot Graph Learning for Molecular Property Prediction},
  author={Guo, Zhichun and Zhang, Chuxu and Yu, Wenhao and Herr, John and Wiest, Olaf and Jiang, Meng and Chawla, Nitesh V},
  booktitle={WWW},
  year={2021}
}