Metabolite discovery through global annotation of untargeted metabolomics data

Liquid chromatography-high-resolution mass spectrometry (LC-MS)-based metabolomics aims to identify and quantify all metabolites, but most LC-MS peaks remain unidentified. Here we present a global network optimization approach, NetID, to annotate untargeted LC-MS metabolomics data. The approach aims...

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Vydané v:	Nature methods Ročník 18; číslo 11; s. 1377 - 1385
Hlavní autori:	Chen, Li, Lu, Wenyun, Wang, Lin, Xing, Xi, Chen, Ziyang, Teng, Xin, Zeng, Xianfeng, Muscarella, Antonio D, Shen, Yihui, Cowan, Alexis, McReynolds, Melanie R, Kennedy, Brandon J, Lato, Ashley M, Campagna, Shawn R, Singh, Mona, Rabinowitz, Joshua D
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States Nature Publishing Group 01.11.2021
Predmet:	Algorithms Animals Annotations Chromatography, Liquid - methods Data Curation - methods Data Curation - standards Fragmentation Global optimization Isotopes Liquid chromatography Liver - metabolism Mass spectrometry Mass spectroscopy Metabolites Metabolome Metabolomics Metabolomics - methods Metabolomics - standards Mice Network management systems Optimization Saccharomyces cerevisiae - metabolism Scientific imaging Spectroscopy Tandem Mass Spectrometry - methods Taurine Thiamine Yeast
ISSN:	1548-7091, 1548-7105, 1548-7105
On-line prístup:	Získať plný text
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