Zinc Molecule Dataset from Constrained Graph Variational Autoencoders for Molecule Design
Liu, Qi and Allamanis, Miltiadis and Brockschmidt, Marc and Gaunt, Alexander L.

250k_rndm_zinc_drugs_clean.zip 33.94MB
Type: Dataset

Metadata:
@article{liu2018constrained,
title= {Zinc Molecule Dataset from Constrained Graph Variational Autoencoders for Molecule Design},
author= {Liu, Qi and Allamanis, Miltiadis and Brockschmidt, Marc and Gaunt, Alexander L.},
journal= {The Thirty-second Conference on Neural Information Processing Systems},
year= {2018},
abstract= {ZINC is a free database of commercially-available compounds for virtual screening. ZINC contains over 230 million purchasable compounds in ready-to-dock, 3D formats. ZINC also contains over 750 million purchasable compounds you can search for analogs in under a minute. Sterling and Irwin, J. Chem. Inf. Model, 2015 http://pubs.acs.org/doi/abs/10.1021/acs.jcim.5b00559

This particular dataset comes from the paper Constrained Graph Variational Autoencoders for Molecule Design, Qi Liu, Miltiadis Allamanis, Marc Brockschmidt, Alexander L. Gaunt. },
keywords= {zinc, graph generation, molecule generation},
terms= {},
license= {},
superseded= {},
url= {https://github.com/Microsoft/constrained-graph-variational-autoencoder}
}

Citation:
Liu, Q., Allamanis, M., Brockschmidt, M., & Gaunt, A. L.. (2018). Zinc Molecule Dataset from Constrained Graph Variational Autoencoders for Molecule Design [Data set]. Academic Torrents. https://academictorrents.com/details/4776b264ca3c4ed05530124b6319ce0d45aff626
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