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Anal Chim Acta. 2016 Mar 31;914:17-34. doi: 10.1016/j.aca.2016.02.001. Epub 2016 Feb 16.

Chemometric methods in data processing of mass spectrometry-based metabolomics: A review.

Author information

1
Yunnan Food Safety Research Institute, Kunming University of Science and Technology, Kunming, 650500, China. Electronic address: yilunzhao@kmust.edu.cn.
2
Department of Applied Biology and Chemical Technology, The Hong Kong Polytechnic University, Hong Kong, 999077, China.
3
College of Chemistry and Chemical Engineering, Central South University, Changsha, 410083, China.
4
College of Animal Science, South China Agricultural University, Guangzhou, 510642, China.
5
Yunnan Food Safety Research Institute, Kunming University of Science and Technology, Kunming, 650500, China.
6
Xiangya Hospital, Central South University, Changsha, 410008, China.

Abstract

This review focuses on recent and potential advances in chemometric methods in relation to data processing in metabolomics, especially for data generated from mass spectrometric techniques. Metabolomics is gradually being regarded a valuable and promising biotechnology rather than an ambitious advancement. Herein, we outline significant developments in metabolomics, especially in the combination with modern chemical analysis techniques, and dedicated statistical, and chemometric data analytical strategies. Advanced skills in the preprocessing of raw data, identification of metabolites, variable selection, and modeling are illustrated. We believe that insights from these developments will help narrow the gap between the original dataset and current biological knowledge. We also discuss the limitations and perspectives of extracting information from high-throughput datasets.

KEYWORDS:

Biomarker; Chemometrics; Data preprocessing; Identification of metabolites; Metabolomics; Modeling

PMID:
26965324
DOI:
10.1016/j.aca.2016.02.001
[Indexed for MEDLINE]

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