CFM-ID 3.0: Significantly Improved ESI-MS/MS Prediction and Compound Identification

CFM-ID 3.0: Significantly Improved ESI-MS/MS Prediction and Compound Identification

Metabolite identification for untargeted metabolomics is often hampered by the lack of experimentally collected reference spectra from tandem mass spectrometry (MS/MS). To circumvent this problem, Competitive Fragmentation Modeling-ID (CFM-ID) was developed to accurately predict electrospray ionizat...

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Bibliographic Details
Main Authors: Yannick Djoumbou-Feunang, Allison Pon, Naama Karu, Jiamin Zheng, Carin Li, David Arndt, Maheswor Gautam, Felicity Allen, David S. Wishart
Format: Article
Language:English
Published: MDPI AG 2019-04-01
Series:Metabolites
Subjects:
mass spectrometry
liquid chromatography
MS spectral prediction
metabolite identification
structure-based chemical classification
rule-based fragmentation
combinatorial fragmentation
Online Access:https://www.mdpi.com/2218-1989/9/4/72

Internet

https://www.mdpi.com/2218-1989/9/4/72

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