NoiseMol

The code of the NoiseAug model. Article: NoiseAug: Data Augmentation via Perturbing Noise for Molecular Property Prediction.

Package description data Dataset used in the experiments in the article

NoiseMol Python files to build a NoiseMol model for molecular property predictions.

Requirements

pytorch 1.7.1

rdkit 2020.09.1

tqdm 4.62.3

python 1.7.1

numpy 1.21.2

Datasets

BACE, BBBP, HIV, Tox21, and ToxCast from MoleculeNet[1], FDA and LogP from ZINC[2]. All the datasets are classification tasks.

Run code

python main.py

Datasets can be changed in the 222 line of main.py.

Reference

[1] Wu, Z., Ramsundar, B., Feinberg, E. N., Gomes, J., Geniesse, C., Pappu, A. S., Leswing, K., and Pande, V. (2018). Moleculenet: a benchmark for molecular machine learning. Chemical science, 9(2), 513–530.

[2] Sterling, T. and Irwin, J. J. (2015). Zinc 15–ligand discovery for everyone. Journal of chemical information and modeling, 55(11), 2324–2337.