Evidence map›Paper›PMID 29140435›Full record

ArticleNucleic acids research2018

HMDB 4.0: the human metabolome database for 2018.

David S Wishart, Yannick Djoumbou Feunang, Ana Marcu, An Chi Guo, Kevin Liang, Rosa Vázquez-Fresno, Tanvir Sajed, Daniel Johnson, Carin Li, Naama Karu and 18 more

Open access · goldAbstract read
In one paragraph

Article in Nucleic acids research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1,828 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1,828citing papers in PubMed, 3 pooled it
135.2field-weighted citation impact, top 1% of its field
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

1,828 citing papers in PubMed, 3 syntheses or guidelines pooled it, 3,505 citations in OpenAlex.

  1. Pooled it
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1,768 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

28 authors at 3 institutions in 2 countries.

David S WishartDepartment of Biological Sciences University of Alberta, Edmonton, AB T6G 2E9, Canada.
Yannick Djoumbou FeunangDepartment of Biological Sciences University of Alberta, Edmonton, AB T6G 2E9, Canada.
Ana MarcuDepartment of Biological Sciences University of Alberta, Edmonton, AB T6G 2E9, Canada.
An Chi GuoDepartment of Biological Sciences University of Alberta, Edmonton, AB T6G 2E9, Canada.
Kevin LiangDepartment of Biological Sciences University of Alberta, Edmonton, AB T6G 2E9, Canada.
Rosa Vázquez-FresnoDepartment of Biological Sciences University of Alberta, Edmonton, AB T6G 2E9, Canada.
Tanvir SajedDepartment of Computing Science, University of Alberta, Edmonton, AB T6G 2E8, Canada.
Daniel JohnsonDepartment of Biological Sciences University of Alberta, Edmonton, AB T6G 2E9, Canada.
Carin LiDepartment of Biological Sciences University of Alberta, Edmonton, AB T6G 2E9, Canada.
Naama KaruDepartment of Biological Sciences University of Alberta, Edmonton, AB T6G 2E9, Canada.
Zinat SayeedaDepartment of Computing Science, University of Alberta, Edmonton, AB T6G 2E8, Canada.
Elvis LoDepartment of Biological Sciences University of Alberta, Edmonton, AB T6G 2E9, Canada.
Nazanin AssempourDepartment of Biological Sciences University of Alberta, Edmonton, AB T6G 2E9, Canada.
Mark BerjanskiiDepartment of Biological Sciences University of Alberta, Edmonton, AB T6G 2E9, Canada.
Sandeep SinghalDepartment of Biological Sciences University of Alberta, Edmonton, AB T6G 2E9, Canada.
David ArndtDepartment of Biological Sciences University of Alberta, Edmonton, AB T6G 2E9, Canada.
Yonjie LiangDepartment of Biological Sciences University of Alberta, Edmonton, AB T6G 2E9, Canada.
Hasan BadranDepartment of Biological Sciences University of Alberta, Edmonton, AB T6G 2E9, Canada.
Jason GrantDepartment of Biological Sciences University of Alberta, Edmonton, AB T6G 2E9, Canada.
Arnau Serra-CayuelaDepartment of Biological Sciences University of Alberta, Edmonton, AB T6G 2E9, Canada.
Yifeng LiuDepartment of Computing Science, University of Alberta, Edmonton, AB T6G 2E8, Canada.
Rupa MandalDepartment of Biological Sciences University of Alberta, Edmonton, AB T6G 2E9, Canada.
Vanessa NeveuInternational Agency for Research on Cancer (IARC), 150 Cours Albert Thomas, 69372 Lyon CEDEX 08, France.
Allison PonDepartment of Biological Sciences University of Alberta, Edmonton, AB T6G 2E9, Canada.
Craig KnoxDepartment of Biological Sciences University of Alberta, Edmonton, AB T6G 2E9, Canada.
Michael WilsonDepartment of Biological Sciences University of Alberta, Edmonton, AB T6G 2E9, Canada.
Claudine ManachInstitut National de la Recherche Agronomique (INRA) - Human Nutrition Unit, Université Clermont Auvergne, F63000 Clermont-Ferrand, France.
Augustin ScalbertInternational Agency for Research on Cancer (IARC), 150 Cours Albert Thomas, 69372 Lyon CEDEX 08, France.
University of Alberta · CACentre International de Recherche sur le Cancer · FRInstitut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement · FR

Funding

World Health Organization 001
6 · The paper itself

Abstract

The Human Metabolome Database or HMDB (www.hmdb.ca) is a web-enabled metabolomic database containing comprehensive information about human metabolites along with their biological roles, physiological concentrations, disease associations, chemical reactions, metabolic pathways, and reference spectra. First described in 2007, the HMDB is now considered the standard metabolomic resource for human metabolic studies. Over the past decade the HMDB has continued to grow and evolve in response to emerging needs for metabolomics researchers and continuing changes in web standards. This year's update, HMDB 4.0, represents the most significant upgrade to the database in its history. For instance, the number of fully annotated metabolites has increased by nearly threefold, the number of experimental spectra has grown by almost fourfold and the number of illustrated metabolic pathways has grown by a factor of almost 60. Significant improvements have also been made to the HMDB's chemical taxonomy, chemical ontology, spectral viewing, and spectral/text searching tools. A great deal of brand new data has also been added to HMDB 4.0. This includes large quantities of predicted MS/MS and GC-MS reference spectral data as well as predicted (physiologically feasible) metabolite structures to facilitate novel metabolite identification. Additional information on metabolite-SNP interactions and the influence of drugs on metabolite levels (pharmacometabolomics) has also been added. Many other important improvements in the content, the interface, and the performance of the HMDB website have been made and these should greatly enhance its ease of use and its potential applications in nutrition, biochemistry, clinical chemistry, clinical genetics, medicine, and metabolomics science.

Indexed as

Databases, FactualMetabolomeDatabases, ChemicalGas Chromatography-Mass SpectrometryHumansMetabolic Networks and PathwaysMetabolomicsNuclear Magnetic Resonance, BiomolecularTandem Mass SpectrometryUser-Computer Interface

Identifiers

PMID29140435
PMCPMC5753273
OpenAlexW2767683865

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.