Evidence map›Paper›PMID 23172809›Full record

ReviewBriefings in bioinformatics2014

Reconciliation of metabolites and biochemical reactions for metabolic networks.

Thomas Bernard, Alan Bridge, Anne Morgat, Sébastien Moretti, Ioannis Xenarios, Marco Pagni

Abstract readReview
In one paragraph

Review in Briefings in bioinformatics, 2014. 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. Article
  2. Article
  3. Article
  4. Article
  5. An overview of graph databases and their applications in the biomedical domain.Database : the journal of biological databases and curation · 2021
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Genome-Scale Metabolic Reconstruction ofFrontiers in microbiology · 2019
    Article
  11. Article
  12. Article
  13. Metabolomics in Plant Priming Research: The Way Forward?International journal of molecular sciences · 2018
    Review
  14. A Genome-Scale Metabolic Model forFrontiers in microbiology · 2018
    Article
  15. Review
  16. Framework and resource for more than 11,000 gene-transcript-protein-reaction associations in human metabolism.Proceedings of the National Academy of Sciences of the United States of America · 2017
    Article
  17. Review
  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

6 authors.

Thomas BernardCorresponding author. Marco Pagni.
Alan Bridge
Anne Morgat
Sébastien Moretti
Ioannis Xenarios
Marco Pagni

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genome-scale metabolic network reconstructions are now routinely used in the study of metabolic pathways, their evolution and design. The development of such reconstructions involves the integration of information on reactions and metabolites from the scientific literature as well as public databases and existing genome-scale metabolic models. The reconciliation of discrepancies between data from these sources generally requires significant manual curation, which constitutes a major obstacle in efforts to develop and apply genome-scale metabolic network reconstructions. In this work, we discuss some of the major difficulties encountered in the mapping and reconciliation of metabolic resources and review three recent initiatives that aim to accelerate this process, namely BKM-react, MetRxn and MNXref (presented in this article). Each of these resources provides a pre-compiled reconciliation of many of the most commonly used metabolic resources. By reducing the time required for manual curation of metabolite and reaction discrepancies, these resources aim to accelerate the development and application of high-quality genome-scale metabolic network reconstructions and models.

Indexed as

Metabolic Networks and PathwaysComputational BiologyComputer SimulationDatabases, FactualGenomicsModels, BiologicalMolecular StructureSoftwarecheminformaticsdata integrationdata interoperabilitymetabolic networksmetabolic resources

Identifiers

PMID23172809
PMCPMC3896926

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.