Metabolomic Science Overview

The science of metabolomics is rapidly growing with our knowledge base of metabolites, tools to perform analyses, and bioinformatics approaches to analyze this data in a constant state of development. With this in mind, we have set up the Metabolomics Science website to provide the metabolomics community a useful platform on the history of metabolism and general information on analytical tools as well as bioinformatics software. We are especially excited about the incorporation of a historic timeline to provide a context for future research.

Analytical Tools

Metabolomic/metabonomic technologies can be classified into one of two categories: Mass Spectrometry (MS) and Nuclear Magnetic Resonance (NMR).

MS is an analytical method comprised of an ion source, a mass analyzer, and a detector that is capable of measuring the mass-to-charge ratio of ions in compounds of a sample. The required sample preparation will affect the physical properties of subsets of the small molecules comprised in a sample; however, it is highly sensitive and when complemented by alternate MS-based technologies can provide a more comprehensive overview of the metabolome. [1]

Diagram of mass spectrometry process

NMR is an analytical method with numerous applications that enables the detection of subatomic and structural information of molecules and demands little sample preparation. It is rapid, requires almost no sample preparation and is a non-destructive analysis; however, it has low sensitivity and provides limited information about chemical identity. [2]

Diagram of nuclear magnetic resonance process

Some of the common platforms used for metabolomics/metabonomics/ metabolite fingerprinting are the following:


  1. Want E.J., Nordstrom A., Morita H., Siuzdak G. From Exogenous to Endogenous: The Inevitable Imprint of Mass Spectrometry in Metabolomics. Journal of Proteome Research, 2007, 6(2), 459-468
  2. Nicholson J.K., Lindon J.C., Holmes E. Metabonomics': understanding the metabolic responses of living systems to pathophysiological stimuli via multivariate statistical analysis of biological NMR spectroscopic data. Journal of Proteome Research, 1999, 29(11), 1181-9

Data Analysis Tools

Metabolite Databases