期刊
JOURNAL OF PROTEOME RESEARCH
卷 4, 期 5, 页码 1485-1492出版社
AMER CHEMICAL SOC
DOI: 10.1021/pr050056y
关键词
metabonomics; H-1-C-13-HMBC NMR; Py-MAB-TOF-MS; statistical integration model; multiple factor analysis
We introduce a statistical approach for integrating data from several analytical platforms. We illustrate this approach using H-1-C-13 Heteronuclear Multiple Bond Connectivity nuclear magnetic resonance spectroscopy (H-1-C-13 HMBC NMR) and Pyrolysis Metastable Atom Bombardment Time-of-Flight mass spectrometry (Py-MAB-TOF-MS) to perform metabolic fingerprinting on cattle treated with anabolic steroids. Multiple factor analysis (MFA) integrates complementary aspects from NMR and MS data into a unique metabolic signature describing the biomarkers related to the dose-response. This work also indicates that, from a practical point of view, metabonomics and other -omics biotechnologies can benefit significantly from a generalized multi-platform integrative approach using multiple factor analysis.
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