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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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Publikationstyp Artikel: Journalartikel
Dokumenttyp Review
Schlagwörter Liquid Chromatography ; Mass Spectrometry ; Metabolite Identification ; Metabolomics ; Retention Time Prediction; Chromatography-mass-spectrometry; Liquid-chromatography; Gas-chromatography; Metabolomics Data; Annotation; Repository; Standards; Tool
Sprache englisch
Veröffentlichungsjahr 2020
HGF-Berichtsjahr 2020
ISSN (print) / ISBN 1615-9306
e-ISSN 1615-9314
Zeitschrift Journal of Separation Science
Quellenangaben Band: 43, Heft: 9-10, Seiten: 1746-1754 Artikelnummer: , Supplement: ,
Verlag Wiley
Verlagsort Postfach 101161, 69451 Weinheim, Germany
Begutachtungsstatus Peer reviewed
Institut(e) Research Unit BioGeoChemistry and Analytics (BGC)
POF Topic(s) 30202 - Environmental Health
Forschungsfeld(er) Environmental Sciences
PSP-Element(e) G-504800-001
DOI 10.1002/jssc.202000060
WOS ID WOS:000535066300010
WOS ID WOS:000523695900001
Scopus ID 85082951302
PubMed ID 32144942
Erfassungsdatum 2020-04-07
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