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.
Original language | English |
---|---|
Pages (from-to) | 17-34 |
Number of pages | 18 |
Journal | Analytica Chimica Acta |
Volume | 914 |
DOIs | |
Publication status | Published - 31 Mar 2016 |
Keywords
- Biomarker
- Chemometrics
- Data preprocessing
- Identification of metabolites
- Metabolomics
- Modeling
ASJC Scopus subject areas
- Analytical Chemistry
- Biochemistry
- Environmental Chemistry
- Spectroscopy