Evidence map›Paper›PMID 26175801›Full record

ArticleJournal of cheminformatics2015

PubChemRDF: towards the semantic annotation of PubChem compound and substance databases.

Gang Fu, Colin Batchelor, Michel Dumontier, Janna Hastings, Egon Willighagen, Evan Bolton

Abstract read
In one paragraph

Article in Journal of cheminformatics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers.

0numbers the graph read from it
0cells of the map it votes in
52citing 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

52 citing papers in PubMed.

  1. tmQM-RDF Data Set: A Knowledge Graph Representing Transition Metal Complexes.Journal of chemical information and modeling · 2026
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  14. Visualization and exploration of linked data using virtual reality.Database : the journal of biological databases and curation · 2024
    Article
  15. Article
  16. Article
  17. Chemical Species Ontology for Data Integration and Knowledge Discovery.Journal of chemical information and modeling · 2023
    Article
  18. Review
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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.

Gang FuNational Center for Biotechnology Information, National Library of Medicine, National Institute of Health, Bethesda, MD USA.
Colin BatchelorRoyal Society of Chemistry, Thomas Graham House, Cambridge, UK.
Michel DumontierStanford Center for Biomedical Informatics Research, Stanford University, Stanford, USA.
Janna HastingsEuropean Molecular Biology Laboratory-European Bioinformatics Institute (EMBL-EBI), Hinxton, UK.
Egon WillighagenDepartment of Bioinformatics-BiGCaT, NUTRIM, Maastricht University, Maastricht, The Netherlands.
Evan BoltonNational Center for Biotechnology Information, National Library of Medicine, National Institute of Health, Bethesda, MD USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPubChem is an open repository for chemical structures, biological activities and biomedical annotations. Semantic Web technologies are emerging as an increasingly important approach to distribute and integrate scientific data. Exposing PubChem data to Semantic Web services may help enable automated data integration and management, as well as facilitate interoperable web applications. DESCRIPTION: This work, one of a series covering the PubChemRDF project, describes an approach to translate PubChem Substance and Compound information into Resource Description Framework (RDF) format. Basic examples are provided to demonstrate its use. The aim of this effort is to provide two new primary benefits to researchers in a cost-effective manner. Firstly, we aim to remove the inherent limitations of using the web-based resource PubChem by allowing a researcher to use readily available semantic technologies (namely, RDF triple stores and their corresponding SPARQL query engines) to query and analyze PubChem data on local computing resources. Secondly, this work intends to help improve data sharing, analysis, and integration of PubChem data to resources external to NCBI and across scientific domains, by means of the association of PubChem data to existing ontological frameworks, including CHEMical INFormation ontology, Semanticscience Integrated Ontology, and others.

conclusionsWith the goal of semantically describing information available in the PubChem archive, pre-existing ontological frameworks were used, rather than creating new ones. Semantic relationships between compounds and substances, chemical descriptors associated with compounds and substances, interrelationships between chemicals, as well as provenance and attribute metadata of substances are described. Graphical abstract:Schematic representation of the semantic links for PubChem compounds and substances.

Identifiers

PMID26175801
PMCPMC4500850

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.