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Training in metabolomics research. II. Processing and statistical analysis of metabolomics data, metabolite identification, pathway analysis, applications of metabolomics and its future
Author(s) -
Barnes Stephen,
Benton H. Paul,
Casazza Krista,
Cooper Sara J.,
Cui Xiangqin,
Du Xiuxia,
Engler Jeffrey,
Kabarowski Janusz H.,
Li Shuzhao,
Pathmasiri Wimal,
Prasain Jeevan K.,
Renfrow Matthew B.,
Tiwari Hemant K.
Publication year - 2016
Publication title -
journal of mass spectrometry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.475
H-Index - 121
eISSN - 1096-9888
pISSN - 1076-5174
DOI - 10.1002/jms.3780
Subject(s) - metabolomics , identification (biology) , metabolite , chemistry , computational biology , data science , computer science , chromatography , biology , biochemistry , ecology
Metabolomics, a systems biology discipline representing analysis of known and unknown pathways of metabolism, has grown tremendously over the past 20 years. Because of its comprehensive nature, metabolomics requires careful consideration of the question(s) being asked, the scale needed to answer the question(s), collection and storage of the sample specimens, methods for extraction of the metabolites from biological matrices, the analytical method(s) to be employed and the quality control of the analyses, how collected data are correlated, the statistical methods to determine metabolites undergoing significant change, putative identification of metabolites and the use of stable isotopes to aid in verifying metabolite identity and establishing pathway connections and fluxes. This second part of a comprehensive description of the methods of metabolomics focuses on data analysis, emerging methods in metabolomics and the future of this discipline. Copyright © 2016 John Wiley & Sons, Ltd.