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Related Concept Videos

NMR Spectrometers: Radiofrequency Pulses and Pulse Sequences01:17

NMR Spectrometers: Radiofrequency Pulses and Pulse Sequences

A pulse is a short burst of radio waves distributed over a range of frequencies that simultaneously excites all the nuclei in the sample. Upon passing a radio frequency pulse along the x-axis, the nuclei absorb energy corresponding to their Larmor frequencies and achieve resonance. This shifts the net magnetization vector from the z-axis toward the transverse plane. This angle of rotation of the magnetization vector, or the flip angle, is proportional to the duration and intensity of the pulse.
NMR Spectrometers: Resolution and Error Correction01:14

NMR Spectrometers: Resolution and Error Correction

When magnetic nuclei in a sample achieve resonance and undergo relaxation, the signal detected in NMR is an approximately exponential free induction decay. Fourier transform of an exponential decay yields a Lorentzian peak in the frequency domain. Lorentzian peaks in an NMR spectrum are defined by their amplitude, full width at half maximum, and position, where the peak width is governed by the spin-spin relaxation time alone. In real experiments, however, the applied magnetic field is rendered...
Fast Fourier Transform01:10

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Interpreting ¹H NMR Signal Splitting: The (n + 1) Rule01:10

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Discrete Fourier Transform01:15

Discrete Fourier Transform

The Discrete Fourier Transform (DFT) is a fundamental tool in signal processing, extending the discrete-time Fourier transform by evaluating discrete signals at uniformly spaced frequency intervals. This transformation converts a finite sequence of time-domain samples into frequency components, each representing complex sinusoids ordered by frequency. The DFT translates these sequences into the frequency domain, effectively indicating the magnitude and phase of each frequency component present...
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Spin systems where the difference in chemical shifts of the coupled nuclei is greater than ten times J are called first-order spin systems. These nuclei are weakly coupled, and their chemical shifts and coupling constant can generally be estimated from the well-separated signals in the spectrum.
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A New Straightforward Method for Lipophilicity (logP) Measurement using 19F NMR Spectroscopy
09:32

A New Straightforward Method for Lipophilicity (logP) Measurement using 19F NMR Spectroscopy

Published on: January 30, 2019

Iterative algorithm of discrete Fourier transform for processing randomly sampled NMR data sets.

Jan Stanek1, Wiktor Koźmiński

  • 1Faculty of Chemistry, University of Warsaw, Pasteura 1, 02-093, Warsaw, Poland.

Journal of Biomolecular NMR
|April 8, 2010
PubMed
Summary
This summary is machine-generated.

This study introduces an iterative algorithm to reduce artifacts in multidimensional Fourier Transformation (MFT) NMR spectra caused by missing data. The method enhances spectral quality for high-dynamic-range analysis, preserving resolution benefits from random sampling.

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Disentangling Glycan-Protein Interactions: Nuclear Magnetic Resonance (NMR) to the Rescue

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Area of Science:

  • Nuclear Magnetic Resonance (NMR) Spectroscopy
  • Computational Chemistry
  • Biophysics

Background:

  • Multidimensional Fourier Transformation (MFT) of sparsely sampled NMR data often leads to artifacts due to missing data.
  • These artifacts can obscure spectral features and hinder accurate analysis, particularly for complex biological molecules.

Purpose of the Study:

  • To investigate the phenomenon of data corruption in MFT NMR spectra from sparse sampling.
  • To develop and detail an effective iterative algorithm for suppressing artifacts in sparse on-grid NMR datasets.
  • To enable the study of high dynamic range NMR spectra while retaining the resolution advantages of random sampling.

Main Methods:

  • Simulations and experimental data were used to investigate artifact formation in MFT NMR.
  • An iterative algorithm incorporating automated peak recognition via statistical methods was developed for artifact suppression.
  • The algorithm was applied to sparse on-grid NMR datasets.

Main Results:

  • The developed iterative algorithm effectively suppresses artifacts in sparsely sampled multidimensional NMR spectra.
  • Automated peak recognition based on statistical methods is integrated into the artifact suppression algorithm.
  • The method allows for the analysis of NMR spectra with high dynamic range, preserving superior resolution in indirectly measured dimensions.

Conclusions:

  • The proposed iterative algorithm is effective for artifact suppression in sparse MFT NMR data.
  • This technique facilitates the study of complex biological systems, such as human ubiquitin, using advanced NMR experiments.
  • The method preserves the benefits of random sampling, leading to enhanced spectral resolution and quality.