Since metabolomics experiments typically produce large amounts of data, sophisticated bioinformatic tools are needed for efficient and high-throughput data processing to remove systematic bias and to explore biologically significant findings.

Mass spectrometry coupled with gas chromatography (GC-MS) or liquid chromatography (LC-MS) are the most common analytical platforms, although capillary electrophoresis mass spectrometry (CE-MS) and nuclear magnetic resonance (NMR) are also widely used in metabolomics research. A number of methods have been developed for the extraction, detection, identification, and quantification of the metabolome. Īs the diversity in abundance and chemical properties of metabolites varies greatly in organisms, a range of analytical techniques must be utilized to survey the entire metabolome.

Through the characterization of metabolite dynamics, interactions, and responses to genetic or environmental perturbations, metabolomics can provide a comprehensive picture of both baseline physiology and global biochemical responses to genetic, abiotic, and biotic factors.

Metabolomics is a rapidly growing discipline focusing on the global study of small molecule metabolites in biological systems.

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