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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 S.,
Benton H. P.,
Casazza K.,
Cooper S. J.,
Cui X.,
Du X.,
Engler J.,
Kabarowski J. H.,
Li S.,
Pathmasiri W.,
Prasain J. K.,
Renfrow M. B.,
Tiwari H. 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.3676
Subject(s) - metabolomics , metabolome , identification (biology) , organism , data science , computational biology , metabolite profiling , chemistry , computer science , biology , chromatography , ecology , paleontology
Metabolomics is perhaps the most challenging of the ‐omics fields, given the complexity of an organism's metabolome and the rapid rate at which it changes. When one sets out to study metabolism there are numerous dynamic variables that can influence metabolism that must be considered. Recognizing the experimental challenges confronting researchers who undertake metabolism studies, workshops like the one at University of Alabama at Birmingham have been established to offer instructional guidance. A summary of the UAB course training materials is being published as a two‐part Special Feature Tutorial. In this month's Part I the authors discuss details of good experimental design and sample collection and handling. In an upcoming Part II, the authors discuss in detail the various aspects of data analysis.