Evidence map›Paper›PMID 25063954›Full record

ArticleJournal of magnetic resonance (San Diego, Calif. : 1997)2014

Accurate scoring of non-uniform sampling schemes for quantitative NMR.

Phillip C Aoto, R Bryn Fenwick, Gerard J A Kroon, Peter E Wright

Abstract read
In one paragraph

Article in Journal of magnetic resonance (San Diego, Calif. : 1997), 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

33 citing papers in PubMed.

  1. Article
  2. Non-Uniform Sampling for Quantitative NOESY.Magnetic resonance in chemistry : MRC · 2025
    Article
  3. Evaluating metrics of spectral quality in nonuniform sampling.Journal of magnetic resonance open · 2025
    Article
  4. Review
  5. Article
  6. Article
  7. NMR methods for the analysis of mixtures.Chemical communications (Cambridge, England) · 2022
    Review
  8. High fidelity sampling schedules for NMR spectra of high dynamic range.Journal of magnetic resonance (San Diego, Calif. : 1997) · 2022
    Article
  9. Clustered sparsity and Poisson-gap sampling.Journal of biomolecular NMR · 2021
    Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Slow Dynamics of Tryptophan-Water Networks in Proteins.Journal of the American Chemical Society · 2018
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Phillip C AotoDepartment of Integrative Structural and Computational Biology and the Skaggs Institute for Chemical Biology, The Scripps Research Institute, La Jolla, CA 92037, United States.
R Bryn FenwickDepartment of Integrative Structural and Computational Biology and the Skaggs Institute for Chemical Biology, The Scripps Research Institute, La Jolla, CA 92037, United States.
Gerard J A KroonDepartment of Integrative Structural and Computational Biology and the Skaggs Institute for Chemical Biology, The Scripps Research Institute, La Jolla, CA 92037, United States.
Peter E WrightDepartment of Integrative Structural and Computational Biology and the Skaggs Institute for Chemical Biology, The Scripps Research Institute, La Jolla, CA 92037, United States. Electronic address: wright@scripps.edu.

Funding

Protein Dynamics in Dihydrofolate Reductase CatalysisR01GM075995 · NIGMS · SCRIPPS RESEARCH INSTITUTE, THE · PI WRIGHT, PETER EDWIN · 2006 to 2021
$6.1M
NIGMS NIH HHS GM75995NIGMS NIH HHS R01 GM075995
6 · The paper itself

Abstract

Non-uniform sampling (NUS) in NMR spectroscopy is a recognized and powerful tool to minimize acquisition time. Recent advances in reconstruction methodologies are paving the way for the use of NUS in quantitative applications, where accurate measurement of peak intensities is crucial. The presence or absence of NUS artifacts in reconstructed spectra ultimately determines the success of NUS in quantitative NMR. The quality of reconstructed spectra from NUS acquired data is dependent upon the quality of the sampling scheme. Here we demonstrate that the best performing sampling schemes make up a very small percentage of the total randomly generated schemes. A scoring method is found to accurately predict the quantitative similarity between reconstructed NUS spectra and those of fully sampled spectra. We present an easy-to-use protocol to batch generate and rank optimal Poisson-gap NUS schedules for use with 2D NMR with minimized noise and accurate signal reproduction, without the need for the creation of synthetic spectra.

Indexed as

AlgorithmsArtifactsData Interpretation, StatisticalModels, StatisticalComputer SimulationMagnetic Resonance SpectroscopyReproducibility of ResultsSample SizeSensitivity and SpecificityNMRNon-uniform samplingNUS scoring functionOptimal NUSPoisson-gap samplingQuantitative NUS

Identifiers

PMID25063954
PMCPMC4165770

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.