Metabolite Identification through Machine Learning— Tackling CASMI Challenge Using FingerID

Metabolite Identification through Machine Learning— Tackling CASMI Challenge Using FingerID

Metabolite identification is a major bottleneck in metabolomics due to the number and diversity of the molecules. To alleviate this bottleneck, computational methods and tools that reliably filter the set of candidates are needed for further analysis by human experts. Recent efforts in assembling la...

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Bibliographic Details
Main Authors: Huibin Shen, Nicola Zamboni, Markus Heinonen, Juho Rousu
Format: Article
Language:English
Published: MDPI AG 2013-06-01
Series:Metabolites
Subjects:
metabolite identification
molecular fingerprints
machine learning
FingerID
Online Access:http://www.mdpi.com/2218-1989/3/2/484

Internet

http://www.mdpi.com/2218-1989/3/2/484

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