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Related Concept Videos

2D NMR: Overview of Heteronuclear Correlation Techniques01:18

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Heteronuclear correlation spectroscopy is an analytical technique that investigates the coupling between different types of nuclei, often a proton and an X-nucleus, such as carbon-13 or nitrogen-15. This method is commonly used in nuclear magnetic resonance (NMR) spectroscopy to gain insights into complex chemical compounds' structural and compositional aspects. A typical heteronuclear correlation spectrum displays X-nucleus chemical shifts on one axis and a proton spectrum on the other...
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Homonuclear correlation spectroscopy (COSY) is a powerful technique used in Nuclear Magnetic Resonance (NMR) spectroscopy to study the correlations between nuclei of the same type within a molecule. It provides information about scalar couplings between adjacent nuclei, which helps determine connectivity and structural information. There are several COSY variants, each with its unique strengths and experimental parameters.
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Homonuclear correlation spectroscopy, or COSY, is a 2-dimensional NMR technique that provides information about coupled protons. Typically, the geminal and vicinal coupling are observed. For example, consider the COSY spectrum of ethyl acetate, where its 1D proton NMR spectrum is plotted along the vertical and horizontal axes with their corresponding chemical shift scale. Three spots on the diagonal corresponding to the three peaks in the 1D proton spectrum are called diagonal peaks. The COSY...
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Related Experiment Video

Updated: May 1, 2026

Author Spotlight: Emerging Technologies and Advanced Tools for Decoding Metabolomics Data Analysis
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Normalization of metabolomics data with applications to correlation maps.

Alexandra Jauhiainen1, Basetti Madhu1, Masako Narita1

  • 1Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, PO Box 281, SE-171 77 Stockholm, Sweden and Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge CB2 0RE, UK.

Bioinformatics (Oxford, England)
|April 9, 2014
PubMed
Summary
This summary is machine-generated.

A new mixed-model normalization method robustly identifies metabolite correlations in metabolomics data. Standardization of nuclear magnetic resonance (NMR) data has minimal impact on correlation discovery, ensuring reliable biological insights.

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Area of Science:

  • Metabolomics
  • Systems Biology
  • Bioinformatics

Background:

  • Metabolomics aims to identify and quantify metabolites, crucial for understanding cellular functions.
  • Metabolite interactions, often studied as correlations, are key to metabolic networks.
  • Existing data normalization methods may hinder accurate correlation estimation.

Purpose of the Study:

  • To develop and validate a novel normalization approach for metabolomics data.
  • To simultaneously estimate metabolite correlations using a mixed-model framework.
  • To assess the impact of calibration standard use in NMR on correlation estimation.

Main Methods:

  • A mixed-model-based normalization approach was developed.
  • Simultaneous estimation of a correlation matrix was integrated into the method.
  • Simulated and real metabolomics data were used for validation.

Main Results:

  • The proposed normalization method demonstrated robustness and high performance in identifying true metabolite correlations.
  • Simulation studies indicated a minor effect of NMR data standardization on correlation discovery.
  • Analysis of real data showed no significant differences in correlation estimates between standardized and non-standardized datasets.

Conclusions:

  • The novel mixed-model normalization approach effectively enhances the discovery of metabolite correlations.
  • Standardization practices in NMR metabolomics have a limited impact on correlation analysis.
  • The method provides a reliable tool for analyzing complex metabolic interactions.