Evidence map›Paper›PMID 27866371›Full record

ArticleJournal of biomolecular NMR2017

Sparse multidimensional iterative lineshape-enhanced (SMILE) reconstruction of both non-uniformly sampled and conventional NMR data.

Jinfa Ying, Frank Delaglio, Dennis A Torchia, Ad Bax

Abstract read
In one paragraph

Article in Journal of biomolecular NMR, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 195 papers.

0numbers the graph read from it
0cells of the map it votes in
195citing 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

195 citing papers in PubMed.

  1. TheBiomolecular NMR assignments · 2026
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  5. Substrate biasing in UCHL5 proteoforms.bioRxiv : the preprint server for biology · 2026
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  9. From bedside to bench: A multimodal approach uncovering the molecular basis of theProceedings of the National Academy of Sciences of the United States of America · 2026
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  10. Protonated Structure of EmrE Reveals C-terminal Tail Gating Mechanism.bioRxiv : the preprint server for biology · 2026
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  17. bioRxiv : the preprint server for biology · 2026
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  18. Review
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135 more citing papers are in PubMed but not listed here.

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.

Jinfa YingLaboratory of Chemical Physics, National Institute of Digestive and Diabetic and Kidney Diseases, National Institutes of Health, Bethesda, MD, 20892, USA. jinfaying@niddk.nih.gov.
Frank DelaglioInstitute for Bioscience and Biotechnology Research, National Institute of Standards and Technology and the University of Maryland, Rockville, MD, 20850, USA.
Dennis A TorchiaNational Institute of Dental and Craniofacial Research, National Institutes of Health, Bethesda, MD, 20892, USA.
Ad BaxLaboratory of Chemical Physics, National Institute of Digestive and Diabetic and Kidney Diseases, National Institutes of Health, Bethesda, MD, 20892, USA. bax@nih.gov.ORCID http://orcid.org/0000-0002-9809-5700

Funding

Methods to accelerate protein structure determination by solution NMRZIADK029046 · NIDDK · NATIONAL INSTITUTE OF DIABETES AND DIGESTIVE AND KIDNEY DISEASES · PI BAX, ADRIAAN · 2009 to 2025
$12.8M
Protein structure and dynamics from residual dipolar couplingsZIADK029048 · NIDDK · NATIONAL INSTITUTE OF DIABETES AND DIGESTIVE AND KIDNEY DISEASES · PI BAX, ADRIAAN · 2009 to 2018
$4.6M
Methods to accelerate protein structure determination by solution NMRZ01DK029046 · NIDDK · NATIONAL INSTITUTE OF DIABETES AND DIGESTIVE AND KIDNEY DISEASES · PI BAX, AD - · 2007 to 2008
$630k
Intramural NIH HHS Z01 DK029046Intramural NIH HHS ZIA DK029046Intramural NIST DOC 9999-NIST
6 · The paper itself

Abstract

Implementation of a new algorithm, SMILE, is described for reconstruction of non-uniformly sampled two-, three- and four-dimensional NMR data, which takes advantage of the known phases of the NMR spectrum and the exponential decay of underlying time domain signals. The method is very robust with respect to the chosen sampling protocol and, in its default mode, also extends the truncated time domain signals by a modest amount of non-sampled zeros. SMILE can likewise be used to extend conventional uniformly sampled data, as an effective multidimensional alternative to linear prediction. The program is provided as a plug-in to the widely used NMRPipe software suite, and can be used with default parameters for mainstream application, or with user control over the iterative process to possibly further improve reconstruction quality and to lower the demand on computational resources. For large data sets, the method is robust and demonstrated for sparsities down to ca 1%, and final all-real spectral sizes as large as 300 Gb. Comparison between fully sampled, conventionally processed spectra and randomly selected NUS subsets of this data shows that the reconstruction quality approaches the theoretical limit in terms of peak position fidelity and intensity. SMILE essentially removes the noise-like appearance associated with the point-spread function of signals that are a default of five-fold above the noise level, but impacts the actual thermal noise in the NMR spectra only minimally. Therefore, the appearance and interpretation of SMILE-reconstructed spectra is very similar to that of fully sampled spectra generated by Fourier transformation.

Indexed as

AlgorithmsComputer SimulationFourier AnalysisNuclear Magnetic Resonance, BiomolecularSensitivity and SpecificitySignal-To-Noise RatioSoftwareTime4D NMRLinear predictionMulti-dimensional NMRNon-uniform samplingNUSSampling schemeSparse samplingSpectral reconstruction

Identifiers

PMID27866371
PMCPMC5438302

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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.