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Determining molecular properties with differential mobility spectrometry and machine learning
- Source :
- Nature Communications, Vol 9, Iss 1, Pp 1-7 (2018)
- Publication Year :
- 2018
- Publisher :
- Nature Portfolio, 2018.
-
Abstract
- The fast and accurate determination of molecular properties is particularly crucial in drug discovery. Here, the authors employ supervised machine learning to treat differential mobility spectrometry – mass spectrometry data for ten classes of drug candidates and predict several condensed-phase properties.
- Subjects :
- Science
Subjects
Details
- Language :
- English
- ISSN :
- 20411723
- Volume :
- 9
- Issue :
- 1
- Database :
- Directory of Open Access Journals
- Journal :
- Nature Communications
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.5545143641641f8afbe1987126bcf2f
- Document Type :
- article
- Full Text :
- https://doi.org/10.1038/s41467-018-07616-w