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Witting, M. ; Böcker, S.*

Current status of retention time prediction in metabolite identification.

J. Sep. Sci. 43, 1746-1754 (2020)
Postprint DOI PMC
Open Access Green
Metabolite identification is a crucial step in nontargeted metabolomics, but also represents one of its current bottlenecks. Accurate identifications are required for correct biological interpretation. To date, annotation and identification are usually based on the use of accurate mass search or tandem mass spectrometry analysis, but neglect orthogonal information such as retention times obtained by chromatographic separation. While several tools are available for the analysis and prediction of tandem mass spectrometry data, prediction of retention times for metabolite identification are not widespread. Here, we review the current state of retention time prediction in liquid chromatography-mass spectrometry-based metabolomics, with a focus on publications published after 2010.
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Publication type Article: Journal article
Document type Review
Keywords Liquid Chromatography ; Mass Spectrometry ; Metabolite Identification ; Metabolomics ; Retention Time Prediction; Chromatography-mass-spectrometry; Liquid-chromatography; Gas-chromatography; Metabolomics Data; Annotation; Repository; Standards; Tool
Language english
Publication Year 2020
HGF-reported in Year 2020
ISSN (print) / ISBN 1615-9306
e-ISSN 1615-9314
Quellenangaben Volume: 43, Issue: 9-10, Pages: 1746-1754 Article Number: , Supplement: ,
Publisher Wiley
Publishing Place Postfach 101161, 69451 Weinheim, Germany
Reviewing status Peer reviewed
POF-Topic(s) 30202 - Environmental Health
Research field(s) Environmental Sciences
PSP Element(s) G-504800-001
Scopus ID 85082951302
PubMed ID 32144942
Erfassungsdatum 2020-04-07