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Nuclear Magnetic Resonance and Statistical Analysis

Nuclear Magnetic Resonance and Electron Spin Resonance Spectroscopy

  1. Tao Ye,
  2. Shucha Zhang,
  3. G. A. Nagana Gowda,
  4. Daniel Raftery

Published Online: 15 DEC 2010

DOI: 10.1002/9780470027318.a9139

Encyclopedia of Analytical Chemistry

Encyclopedia of Analytical Chemistry

How to Cite

Ye, T., Zhang, S., Gowda, G. A. N. and Raftery, D. 2010. Nuclear Magnetic Resonance and Statistical Analysis. Encyclopedia of Analytical Chemistry.

Author Information

  1. Purdue University, Department of Chemistry, West Lafayette, IN, USA

Publication History

  1. Published Online: 15 DEC 2010

Abstract

The impressive high resolution of nuclear magnetic resonance (NMR), its large dynamic range, and especially robust reproducibility lend themselves to advanced statistical methods that can be harnessed to analyze a large variety of complex samples. The primary example of this approach is in the rapidly expanding field of metabolomics that is focused on better understanding systems biology and for the identification of biomarkers of various biological states. In metabolomics, a large number of small-molecule metabolites from body fluids or tissues are detected quantitatively in a single step, and then analyzed with multivariate statistical methods to yield information that is essential for systems biology, drug discovery, early disease diagnosis, toxicology, food and nutrition sciences, and other studies. NMR-based metabolomic studies have been very successful due to the high quality and reliability of the methodology. In this article, we summarize the major experimental and statistical methods used in combining NMR and advanced statistical analyses especially in metabolomics along with a description of some important applications.

Keywords:

  • NMR spectroscopy;
  • multivariate statistical analysis;
  • metabolomics;
  • metabonomics;
  • metabolic profiling;
  • biomarker;
  • early detection