A semantic web ontology for small molecules and their biological targets

Choi, JooYoung, Davis, Melissa J., Newman, Andrew F. and Ragan, Mark A. (2010) A semantic web ontology for small molecules and their biological targets. Journal of Chemical Information and Modeling, 50 5: 732-741. doi:10.1021/ci900461j


Author Choi, JooYoung
Davis, Melissa J.
Newman, Andrew F.
Ragan, Mark A.
Title A semantic web ontology for small molecules and their biological targets
Journal name Journal of Chemical Information and Modeling   Check publisher's open access policy
ISSN 1549-9596
1549-960X
0095-2338
Publication date 2010-05-24
Sub-type Article (original research)
DOI 10.1021/ci900461j
Volume 50
Issue 5
Start page 732
End page 741
Total pages 10
Editor William L. Jorgensen
Place of publication Washington, DC, U.S.A.
Publisher American Chemical Society
Language eng
Formatted abstract
A wide range of data on sequences, structures, pathways, and networks of genes and gene products is available for hypothesis testing and discovery in biological and biomedical research. However, data describing the physical, chemical, and biological properties of small molecules have not been well-integrated with these resources. Semantically rich representations of chemical data, combined with Semantic Web technologies, have the potential to enable the integration of small molecule and biomolecular data resources, expanding the scope and power of biomedical and pharmacological research. We employed the Semantic Web technologies Resource Description Framework (RDF) and Web Ontology Language (OWL) to generate a Small Molecule Ontology (SMO) that represents concepts and provides unique identifiers for biologically relevant properties of small molecules and their interactions with biomolecules, such as proteins. We instanced SMO using data from three public data sources, i.e., DrugBank, PubChem and UniProt, and converted to RDF triples. Evaluation of SMO by use of predetermined competency questions implemented as SPARQL queries demonstrated that data from chemical and biomolecular data sources were effectively represented and that useful knowledge can be extracted. These results illustrate the potential of Semantic Web technologies in chemical, biological, and pharmacological research and in drug discovery.
© 2010 American Chemical Society
Keyword Systems biology
Bioinformatics
Discovery
Database
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2011 Collection
Institute for Molecular Bioscience - Publications
 
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Created: Sun, 06 Jun 2010, 10:05:07 EST