化学
量子化学
代谢组
纳米技术
鉴定(生物学)
分子
生化工程
代谢组学
计算化学
有机化学
色谱法
材料科学
植物
工程类
生物
作者
Ricardo M. Borges,Sean Colby,Susanta Das,Arthur S. Edison,Oliver Fiehn,Tobias Kind,Jesi Lee,Amy T. Merrill,Kenneth M. Merz,Thomas Metz,Jamie Nuñez,Dean J. Tantillo,Lee‐Ping Wang,Shunyang Wang,Ryan Renslow
出处
期刊:Chemical Reviews
[American Chemical Society]
日期:2021-05-12
卷期号:121 (10): 5633-5670
被引量:69
标识
DOI:10.1021/acs.chemrev.0c00901
摘要
A primary goal of metabolomics studies is to fully characterize the small-molecule composition of complex biological and environmental samples. However, despite advances in analytical technologies over the past two decades, the majority of small molecules in complex samples are not readily identifiable due to the immense structural and chemical diversity present within the metabolome. Current gold-standard identification methods rely on reference libraries built using authentic chemical materials ("standards"), which are not available for most molecules. Computational quantum chemistry methods, which can be used to calculate chemical properties that are then measured by analytical platforms, offer an alternative route for building reference libraries,
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