MESSAR: Automated recommendation of metabolite substructures from tandem mass spectra
Published 2020 View Full Article
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Title
MESSAR: Automated recommendation of metabolite substructures from tandem mass spectra
Authors
Keywords
Metabolites, Drug metabolism, Mass spectra, Statistical data, Metabolic networks, Metabolomics, Machine learning algorithms, Molecular structure
Journal
PLoS One
Volume 15, Issue 1, Pages e0226770
Publisher
Public Library of Science (PLoS)
Online
2020-01-17
DOI
10.1371/journal.pone.0226770
References
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- (2016) David S. Wishart NATURE REVIEWS DRUG DISCOVERY
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