Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/61858
Title: Chemometric methods in data processing of mass spectrometry-based metabolomics : a review
Authors: Yi, L
Dong, N
Yun, Y
Deng, B
Ren, D
Liu, S
Liang, Y
Keywords: Biomarker
Chemometrics
Data preprocessing
Identification of metabolites
Metabolomics
Modeling
Issue Date: 2016
Publisher: Elsevier
Source: Analytica chimica acta, 2016, v. 914, p. 17-34 How to cite?
Journal: Analytica chimica acta 
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.
URI: http://hdl.handle.net/10397/61858
ISSN: 0003-2670
DOI: 10.1016/j.aca.2016.02.001
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