Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models.

ABSTRACT: Generative models are becoming a tool of choice for exploring the molecular space. These models learn on a large training dataset and produce novel molecular structures with similar properties. Generated structures can be utilized for virtual screening or training semi-supervized predictive models in the downstream tasks. While there are plenty of generative models, it is unclear how to compare and rank them. In this work, we introduce a benchmarking platform called Molecular Sets (MOSES) to standardize training and comparison of molecular generative models. MOSES provides training and testing datasets, and a set of metrics to evaluate the quality and diversity of generated structures. We have implemented and compared several molecular generation models and suggest to use our results as re

SUBMITTER: Polykovskiy D 

PROVIDER: S-EPMC7775580 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature