Evidence map›Paper›PMID 21398670›Full record

ArticleBioinformatics (Oxford, England)2011

Identification and quantification of metabolites in (1)H NMR spectra by Bayesian model selection.

Cheng Zheng, Shucha Zhang, Susanne Ragg, Daniel Raftery, Olga Vitek

Abstract readEvaluation Study
In one paragraph

Article in Bioinformatics (Oxford, England), 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.

0numbers the graph read from it
0cells of the map it votes in
39citing 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

39 citing papers in PubMed.

  1. UntargetedTranslational psychiatry · 2026
    Article
  2. Review
  3. Article
  4. Applications of chromatographic methods in metabolomics: A review.Journal of chromatography. B, Analytical technologies in the biomedical and life sciences · 2024
    Review
  5. Article
  6. Extended automated quantification algorithm (AQuA) for targetedMetabolomics : Official journal of the Metabolomic Society · 2023
    Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Practical Aspects of NMR-Based Metabolomics.Handbook of experimental pharmacology · 2023
    Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. 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

5 authors.

Cheng ZhengDepartment of Statistics, Purdue University, West Lafayette, IN 47907, USA. zhengc@purdue.edu
Shucha Zhang
Susanne Ragg
Daniel Raftery
Olga Vitek

Funding

INDIANA CLINICAL AND TRANSLATIONAL SCIENCE INSTITUTE (UL1): BPCAUL1RR025761 · NCRR · INDIANA UNIVERSITY INDIANAPOLIS · PI SHEKHAR, ANANTHA · 2008 to 2011
$21.0M
Advanced Methods in NMR-Based MetabolomicsR01GM085291 · NIGMS · UNIVERSITY OF WASHINGTON · PI RAFTERY, DANIEL · 2008 to 2016
$2.7M
Mentored Patient-Oriented Research Career Development AwardK23RR019540 · NCRR · INDIANA UNIV-PURDUE UNIV AT INDIANAPOLIS · PI RAGG, SUSANNE · 2004 to 2008
$671k
NCRR NIH HHS 5K23RR019540NCRR NIH HHS UL1RR025761NIGMS NIH HHS R01GM085291
6 · The paper itself

Abstract

motivationNuclear magnetic resonance (NMR) spectroscopy is widely used for high-throughput characterization of metabolites in complex biological mixtures. However, accurate interpretation of the spectra in terms of identities and abundances of metabolites can be challenging, in particular in crowded regions with heavy peak overlap. Although a number of computational approaches for this task have recently been proposed, they are not entirely satisfactory in either accuracy or extent of automation.

resultsWe introduce a probabilistic approach Bayesian Quantification (BQuant), for fully automated database-based identification and quantification of metabolites in local regions of (1)H NMR spectra. The approach represents the spectra as mixtures of reference profiles from a database, and infers the identities and the abundances of metabolites by Bayesian model selection. We show using a simulated dataset, a spike-in experiment and a metabolomic investigation of plasma samples that BQuant outperforms the available automated alternatives in accuracy for both identification and quantification. AVAILABILITY: The R package BQuant is available at: http://www.stat.purdue.edu/~ovitek/BQuant-Web/.

Indexed as

Bayes TheoremHumansMagnetic Resonance SpectroscopyMaleMetabolomicsModels, Statistical

Identifiers

PMID21398670
PMCPMC3106181

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.