Evidence map›Paper›PMID 26847574›Full record

ArticleJournal of biomolecular NMR2016

Non-uniform sampling of NMR relaxation data.

Troels E Linnet, Kaare Teilum

Abstract read
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In one paragraph

Article in Journal of biomolecular NMR, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

  1. Article
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  6. Article
  7. Boosting the resolution of low-fieldJournal of biomolecular NMR · 2020
    Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Measurement of protein backboneJournal of biomolecular NMR · 2017
    Article
  16. Article
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  18. 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

2 authors.

Troels E LinnetSBiNLab and the Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Ole Maaløes Vej 5, 2200, Copenhagen N, Denmark.
Kaare TeilumSBiNLab and the Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Ole Maaløes Vej 5, 2200, Copenhagen N, Denmark. kaare.teilum@bio.ku.dk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The use of non-uniform sampling of NMR spectra may give significant reductions in the data acquisition time. For quantitative experiments such as the measurement of spin relaxation rates, non-uniform sampling is however not widely used as inaccuracies in peak intensities may lead to errors in the extracted dynamic parameters. By systematic reducing the coverage of the Nyquist grid of (15)N Carr-Purcell-Meiboom-Gill (CPMG) relaxation dispersion datasets for four different proteins and performing a full data analysis of the resulting non-uniform sampled datasets, we have compared the performance of the multi-dimensional decomposition and iterative re-weighted least-squares algorithms in reconstructing spectra with accurate peak intensities. As long as a single fully sampled spectrum is included in a series of otherwise non-uniform sampled two-dimensional spectra, multi-dimensional decomposition reconstructs the non-uniform sampled spectra with high accuracy. For two of the four analyzed datasets, a coverage of only 20% results in essentially the same results as the fully sampled data. As exemplified by other data, such a low coverage is in general not enough to produce reliable results. We find that a coverage level not compromising the final results can be estimated by recording a single full two-dimensional spectrum and reducing the spectrum quality in silico.

Indexed as

Databases, ProteinNuclear Magnetic Resonance, BiomolecularMulti-dimensional decompositionNon-uniform samplingProtein NMRRelaxation dispersion

Identifiers

What OpenQuestion holds

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Registered trials

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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.