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Related Concept Videos

2D NMR: Overview of Homonuclear Correlation Techniques01:16

2D NMR: Overview of Homonuclear Correlation Techniques

332
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.
COSY90 is the standard two-dimensional (2D) COSY experiment that...
332
2D NMR: Overview of Heteronuclear Correlation Techniques01:18

2D NMR: Overview of Heteronuclear Correlation Techniques

370
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...
370
Applications Of NMR In Biology01:25

Applications Of NMR In Biology

4.0K
Nuclear magnetic resonance (NMR) spectroscopy is a very valuable analytical technique for researchers. It has been used for more than 50 years as an analytical tool. F. Bloch and E. Purcell formulated NMR in 1946 and won the 1952 Nobel Prize in Physics  for their work. Biological macromolecules such as proteins, nucleic acids, lipids, and organic molecules including pharmaceutical compounds, can be studied using this versatile tool that exploits the magnetic properties of certain nuclei.
4.0K
¹H NMR Signal Integration: Overview00:58

¹H NMR Signal Integration: Overview

2.1K
The intensity of a signal, which can be represented by the area under the peak, depends on the number of protons contributing to that signal. The area under each peak is shown as a vertical line called an integral, with the integral value listed under it, as seen in the proton NMR spectrum of benzyl acetate. Each integral value is divided by the smallest integral value to obtain the ratio of the number of protons producing each signal. The ratio reveals the relative number of protons and not...
2.1K
¹H NMR Signal Multiplicity: Splitting Patterns01:13

¹H NMR Signal Multiplicity: Splitting Patterns

5.5K
When protons A and X are coupled, their nuclear spin energy levels are slightly modified. This is because the energy required to excite proton A to a spin state parallel to proton X is slightly different from the energy required for it to become anti-parallel to spin X. Consequently, there are two possible excitation frequencies for A (A1 and A2), depending on the spin state of X, and vice versa. The mutual nature of coupling implies that the difference between frequencies A1 and A2, indicated...
5.5K
NMR Spectrometers: Overview01:20

NMR Spectrometers: Overview

1.4K
NMR spectrometers consist of a strong magnet, a radiofrequency transmitter, and a detector attached to a computer console for recording spectra of samples containing NMR-active nuclei. In first-generation NMR instruments called continuous-wave spectrometers, the resonance frequencies of the nuclei are determined by frequency-sweep or field-sweep methods. The magnetic field strength is fixed and the rf signal is swept in the former, while the radiofrequency signal is fixed and the magnetic field...
1.4K

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Related Experiment Video

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Identification and Quantification of Deranged Metabolites in Critically Ill Patients Using NMR-Based Metabolomics
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Identification and Quantification of Deranged Metabolites in Critically Ill Patients Using NMR-Based Metabolomics

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Multivariate analysis of NMR-based metabolomic data.

Julia Debik1, Matteo Sangermani1, Feng Wang1,2

  • 1Department of Circulation and Medical Imaging, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology-NTNU, Trondheim, Norway.

NMR in Biomedicine
|November 5, 2021
PubMed
Summary

This review covers multivariate statistical and machine learning methods for analyzing nuclear magnetic resonance (NMR) metabolomic data. It highlights techniques that account for metabolite correlations for deeper biological insights.

Keywords:
ASCAPCAPLS-DAclusteringdeep learningmachine learningvalidation

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Area of Science:

  • Metabolomics
  • Biochemistry
  • Data Science

Background:

  • Nuclear magnetic resonance (NMR) spectroscopy is crucial for detecting metabolites and lipids.
  • Metabolites function in complex networks, exhibiting high correlations.
  • Understanding these correlations is key for optimal biological insight.

Purpose of the Study:

  • To review current state-of-the-art multivariate methods for NMR-based metabolomic data analysis.
  • To discuss alternative statistical and machine learning approaches.
  • To highlight the strengths and limitations of various analytical methods.

Main Methods:

  • Latent-variable-based methods like Principal Component Analysis (PCA) and Partial Least-Squares Discriminant Analysis (PLS-DA) are commonly used.
  • Traditional statistical approaches are increasingly applied with larger datasets.
  • Alternative machine learning methods are gaining traction for analyzing quantified metabolite levels.

Main Results:

  • The review provides an overview of multivariate techniques for NMR metabolomics.
  • It compares traditional statistical methods with newer machine learning approaches.
  • Strengths and limitations of each method are discussed in the context of large population cohorts.

Conclusions:

  • The choice of method depends on the specific research question and data characteristics.
  • Accounting for metabolite correlations is essential for robust metabolomic analysis.
  • The field is evolving with the integration of advanced statistical and machine learning tools.