作者
Zhiwei Zhou, Jia Tu, Zheng-Jiang Zhu
发表日期
2018/2/1
来源
Current Opinion in Chemical Biology
卷号
42
页码范围
34-41
出版商
Elsevier Current Trends
简介
Highlights
- Ion mobility–mass spectrometry (IM–MS) supports the metabolomics and lipidomics applications.
- Collision cross-section (CCS) value is a valuable physiochemical property for metabolite/lipid identification.
- Machine-learning based prediction generates the CCS values in a large scale to facilitate IM–MS based metabolomics and lipidomics.
Metabolomics and lipidomics aim to comprehensively measure the dynamic changes of all metabolites and lipids that are present in biological systems. The use of ion mobility–mass spectrometry (IM–MS) for metabolomics and lipidomics has facilitated the separation and the identification of metabolites and lipids in complex biological samples. The collision cross-section (CCS) value derived from IM–MS is a valuable physiochemical property for the unambiguous identification of metabolites and lipids. However, CCS values obtained from experimental measurement and …
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Z Zhou, J Tu, ZJ Zhu - Current Opinion in Chemical Biology, 2018