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GraSeq: Graph and Sequence Fusion Learning for Molecular Property Prediction. In CIKM 2020.

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GraSeq: Graph and Sequence Fusion Learning for Molecular Property Prediction

Introduction

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

GraSeq: Graph and Sequence Fusion Learning for Molecular Property Prediction. In CIKM 2020.

Contact Zhichun Guo (zguo5@nd.edu), if you have any questions.

Usage

Installation

- torch >= 1.0.0
- sklearn >= 0.21.0
- rdkit.Chem 

Run code

  • For single-task classification (such as LogP, FDA, BBBP, BACE datasets):
    python GraSeq_single/main.py
    
  • For multi-task classification (such as Tox21 and ToxCast datasets):
    python GraSeq_multi/main.py
    

Reference

@inproceedings{guo2020graseq,
  title={GraSeq: Graph and Sequence Fusion Learning for Molecular Property Prediction},
  author={Guo, Zhichun and Yu, Wenhao and Zhang, Chuxu and Jiang, Meng and Chawla, Nitesh V},
  booktitle={Proceedings of the 29th ACM International Conference on Information \& Knowledge Management},
  pages={435--443},
  year={2020}
}

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GraSeq: Graph and Sequence Fusion Learning for Molecular Property Prediction. In CIKM 2020.

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