Show simple item record Wild, David J. Ding, Ying Chen, Bin 2012-04-09T17:30:46Z 2012-04-09T17:30:46Z 2012-03-08
dc.identifier.citation Chen, B., Ding, Y., & Wild, D.J (2012). Improving integrative searching of systems chemical biology data using semantic annotation. Journal of Cheminformatics. 4(3). en
dc.identifier.uri en
dc.description.abstract Background: Systems chemical biology and chemogenomics are considered critical, integrative disciplines in modern biomedical research, but require data mining of large, integrated, heterogeneous datasets from chemistry and biology. We previously developed an RDF-based resource called Chem2Bio2RDF that enabled querying of such data using the SPARQL query language. Whilst this work has proved useful in its own right as one of the first major resources in these disciplines, its utility could be greatly improved by the application of an ontology for annotation of the nodes and edges in the RDF graph, enabling a much richer range of semantic queries to be issued. Results: We developed a generalized chemogenomics and systems chemical biology OWL ontology called Chem2Bio2OWL that describes the semantics of chemical compounds, drugs, protein targets, pathways, genes, diseases and side-effects, and the relationships between them. The ontology also includes data provenance. We used it to annotate our Chem2Bio2RDF dataset, making it a rich semantic resource. Through a series of scientific case studies we demonstrate how this (i) simplifies the process of building SPARQL queries, (ii) enables useful new kinds of queries on the data and (iii) makes possible intelligent reasoning and semantic graph mining in chemogenomics and systems chemical biology. Availability: Chem2Bio2OWL is available at The document is available at http:// en
dc.language.iso en_US en
dc.publisher Chemistry Central Ltd. en
dc.rights © 2012 Chen et al; licensee Chemistry Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. en
dc.title Improving integrative searching of systems chemical biology data using semantic annotation en
dc.type Article en

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