AntDAS: Automatic Data Analysis Strategy for UPLC–QTOF-Based Nontargeted Metabolic Profiling Analysis-Reference-Cited by-同舟云学术

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AntDAS: Automatic Data Analysis Strategy for UPLC–QTOF-Based Nontargeted Metabolic Profiling Analysis

Published:2017-09-27 Issue:20 Volume:89 Page:11083-11090
ISSN:0003-2700
Container-title:Analytical Chemistry
language:en
Short-container-title:Anal. Chem.

Author:

Fu Hai-Yan¹^ORCID,Guo Xiao-Ming¹,Zhang Yue-Ming,Song Jing-Jing²,Zheng Qing-Xia³,Liu Ping-Ping³,Lu Peng³,Chen Qian-Si³,Yu Yong-Jie^ORCID,She Yuanbin⁴

Affiliation:

1. School of Pharmaceutical Sciences, South Central University for Nationalities, Wuhan 430074, China

2. Ningxia Institute of Cultural Relics and Archeology, Yinchuan 750001, China

3. China Tobacco Gene Research Center, Zhengzhou Tobacco Research Institute of CNTC, Zhengzhou 450001, China

4. ZhengJiang University of Technology, Hangzhou 310014, China

Funder

Ministry of Science and Technology of the People's Republic of China

National Natural Science Foundation of China

Hubei Province

Publisher

American Chemical Society (ACS)

Subject

Analytical Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.analchem.7b03160

Reference45 articles.

1. PlantMAT: A Metabolomics Tool for Predicting the Specialized Metabolic Potential of a System and for Large-Scale Metabolite Identifications

2. Discovering Regulated Metabolite Families in Untargeted Metabolomics Studies

3. Mass spectrometry in plant metabolomics strategies: from analytical platforms to data acquisition and processing

4. Global metabolic profiling procedures for urine using UPLC–MS

5. Current state-of-the-art of nontargeted metabolomics based on liquid chromatography–mass spectrometry with special emphasis in clinical applications

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