Evidence map›Paper›PMID 22833055›Full record

ArticleJournal of biomolecular NMR2012

Compressed sensing reconstruction of undersampled 3D NOESY spectra: application to large membrane proteins.

Mark J Bostock, Daniel J Holland, Daniel Nietlispach

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Article in Journal of biomolecular NMR, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

23 citing papers in PubMed.

  1. Backbone and side‑chainBiomolecular NMR assignments · 2025
    Article
  2. A DNA condensation code for linker histones.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  3. Article
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  5. Clustered sparsity and Poisson-gap sampling.Journal of biomolecular NMR · 2021
    Article
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  15. A new approach to compressed sensing for NMR.Magnetic resonance in chemistry : MRC · 2015
    Article
  16. Article
  17. Compressed sensing to accelerate magnetic resonance spectroscopic imaging: evaluation and application to 23Na-imaging of mouse hearts.Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance · 2015
    Article
  18. Sensitivity of nonuniform sampling NMR.The journal of physical chemistry. B · 2015
    Article
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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

3 authors.

Mark J BostockDepartment of Biochemistry, University of Cambridge, Cambridge, UK.
Daniel J Holland
Daniel Nietlispach

Funding

Biotechnology and Biological Sciences Research Council BB/G011915/1
6 · The paper itself

Abstract

Central to structural studies of biomolecules are multidimensional experiments. These are lengthy to record due to the requirement to sample the full Nyquist grid. Time savings can be achieved through undersampling the indirectly-detected dimensions combined with non-Fourier Transform (FT) processing, provided the experimental signal-to-noise ratio is sufficient. Alternatively, resolution and signal-to-noise can be improved within a given experiment time. However, non-FT based reconstruction of undersampled spectra that encompass a wide signal dynamic range is strongly impeded by the non-linear behaviour of many methods, which further compromises the detection of weak peaks. Here we show, through an application to a larger α-helical membrane protein under crowded spectral conditions, the potential use of compressed sensing (CS) l (1)-norm minimization to reconstruct undersampled 3D NOESY spectra. Substantial signal overlap and low sensitivity make this a demanding application, which strongly benefits from the improvements in signal-to-noise and resolution per unit time achieved through the undersampling approach. The quality of the reconstructions is assessed under varying conditions. We show that the CS approach is robust to noise and, despite significant spectral overlap, is able to reconstruct high quality spectra from data sets recorded in far less than half the amount of time required for regular sampling.

Indexed as

AlgorithmsFourier AnalysisImage Processing, Computer-AssistedMembrane ProteinsNuclear Magnetic Resonance, BiomolecularSignal Processing, Computer-AssistedSignal-To-Noise RatioMembrane Proteins

Identifiers

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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.