期刊
JOURNAL OF CHROMATOGRAPHY B-ANALYTICAL TECHNOLOGIES IN THE BIOMEDICAL AND LIFE SCIENCES
卷 871, 期 2, 页码 191-201出版社
ELSEVIER
DOI: 10.1016/j.jchromb.2008.04.049
关键词
quantitative systems biology; high-throughput omic techniques; data correction and normalization; data validation; derivatization biases; TMS-derivatives; methoximation; metabolite extraction
资金
- US NSF [QSB-0331312]
- UMD Minta-Martin Foundation
- UMD Chemical and Biomolecular Engineering Department
- FORTH/ICE-HT
- European Network of Excellence
Metabolomics being the most recently introduced omic analytical platform is currently at its development phase. For the metabolomics to be broadly deployed to biological and clinical research and practice, issues regarding data validation and reproducibility need to be resolved. Gas chromatography-mass spectrometry (GC-MS) will remain integral part of the metabolomics laboratory. In this paper, the sources of biases in GC-MS metabolomics are discussed and experimental evidence for their Occurrence and impact on the final results is provided. When available, methods to correct or account for these biases are presented towards the standardization of a systematic methodology for quantitative GC-MS metabolomics. (C) 2008 Elsevier B.V. All rights reserved.
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