Evidence map›Paper›PMID 25750701›Full record

ArticleComputational and structural biotechnology journal2015

A new paradigm for known metabolite identification in metabonomics/metabolomics: metabolite identification efficiency.

Jeremy R Everett

Abstract read
In one paragraph

Article in Computational and structural biotechnology journal, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing 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

21 citing papers in PubMed.

  1. Article
  2. Review
  3. Problems, principles and progress in computational annotation of NMR metabolomics data.Metabolomics : Official journal of the Metabolomic Society · 2022
    Review
  4. Article
  5. Article
  6. The Zebra Mussel (Metabolites · 2020
    Article
  7. Article
  8. Article
  9. Optimizing 1DMetabolomics : Official journal of the Metabolomic Society · 2019
    Review
  10. Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. The future of NMR-based metabolomics.Current opinion in biotechnology · 2017
    Review
  18. Review
  19. Navigating freely-available software tools for metabolomics analysis.Metabolomics : Official journal of the Metabolomic Society · 2017
    Review
  20. Review
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

1 author.

Jeremy R EverettMedway Metabonomics Research Group, University of Greenwich, Chatham Maritime, Kent ME4 4TB, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A new paradigm is proposed for assessing confidence in the identification of known metabolites in metabonomics studies using NMR spectroscopy approaches. This new paradigm is based upon the analysis of the amount of metabolite identification information retrieved from NMR spectra relative to the molecular size of the metabolite. Several new indices are proposed including: metabolite identification efficiency (MIE) and metabolite identification carbon efficiency (MICE), both of which can be easily calculated. These indices, together with some guidelines, can be used to provide a better indication of known metabolite identification confidence in metabonomics studies than existing methods. Since known metabolite identification in untargeted metabonomics studies is one of the key bottlenecks facing the science currently, it is hoped that these concepts based on molecular spectroscopic informatics, will find utility in the field.

Indexed as

Metabolite identification carbon efficiency (MICE)Metabolite identification efficiency (MIE)MetabolomicsMetabonomicsMolecular spectroscopic informationNMR spectroscopy

Identifiers

PMID25750701
PMCPMC4348432

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.