Masked graph modeling for molecule generation

Generating new sensible molecular structures is a key problem in computer aided drug discovery. Here the authors propose a graph-based molecular generative model that outperforms previously proposed graph-based generative models of molecules and performs comparably to several SMILES-based models.

Bibliographic Details
Main Authors: Omar Mahmood, Elman Mansimov, Richard Bonneau, Kyunghyun Cho
Format: Article
Language:English
Published: Nature Portfolio 2021-05-01
Series:Nature Communications
Online Access:https://doi.org/10.1038/s41467-021-23415-2