Machine learning for chemical discovery.
editorial · Level V
Where this comes from
- Record sourced from PubMed, PMID 32807794.
- Also identified by DOI 10.1038/s41467-020-17844-8 and PMC identifier 7431574.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
Abstract
Discovering chemicals with desired attributes is a long and painstaking process. Curated datasets containing reliable quantum-mechanical properties for millions of molecules are becoming increasingly available. The development of novel machine learning tools to obtain chemical knowledge from these datasets has the potential to revolutionize the process of chemical discovery. Here, I comment on recent breakthroughs in this emerging field and discuss the challenges for the years to come.