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

By Gang Fu, Colin R. Batchelor, M. Dumontier, Janna Hastings, Egon Willighagen, Evan E. Bolton. 2015

112 citations recorded by the source corpus.

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.DescriptionThis 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.

Subfields: Artificial Intelligence, Information Systems and Management, Molecular Biology

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

In Information Systems and Management

Axel Drefahl

In Molecular Biology

Citations in the corpus

PubChem Substance and Compound databases (2015, methodology): “gov/rdf/) (35) encodes PubChem’s data using the Resource Description Framework (RDF) (http://www.”
Database resources of the National Center for Biotechnology Information in 2025. (2024, unknown): “Moreover, the co-occurrence data from the literature knowledge panel are also made available in PubChemRDF ( 36 ), which is machine-readable PubChem data formatted using the Resource Description Framework.”
YummyData: providing high-quality open life science data (2018, background): “Similarly, the National Center for Biotechnology Information provides RDF versions of MeSH (5) and PubChem (6).”
ChEBI in 2016: Improved services and an expanding collection of metabolites (2015, methodology): “example the recent representation of the PubChem database content as RDF used ChEBI classes where possible to provide the rdf:type classification for the PubChem chemicals in their RDF representation (10).”