Improving integrative searching of systems chemical biology data using semantic annotation
<p>Abstract</p> <p>Background</p> <p>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...
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| Format: | Article |
| Language: | English |
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BMC
2012-03-01
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| Series: | Journal of Cheminformatics |
| Online Access: | http://www.jcheminf.com/content/4/1/6 |
| _version_ | 1818760384904953856 |
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| author | Chen Bin Ding Ying Wild David J |
| author_facet | Chen Bin Ding Ying Wild David J |
| author_sort | Chen Bin |
| collection | DOAJ |
| description | <p>Abstract</p> <p>Background</p> <p>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.</p> <p>Results</p> <p>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.</p> <p>Availability</p> <p>Chem2Bio2OWL is available at <url>http://chem2bio2rdf.org/owl</url>. The document is available at <url>http://chem2bio2owl.wikispaces.com</url>.</p> |
| first_indexed | 2024-12-18T06:57:46Z |
| format | Article |
| id | doaj.art-01b060231d4f4c70aa449134a9963c5a |
| institution | Directory Open Access Journal |
| issn | 1758-2946 |
| language | English |
| last_indexed | 2024-12-18T06:57:46Z |
| publishDate | 2012-03-01 |
| publisher | BMC |
| record_format | Article |
| series | Journal of Cheminformatics |
| spelling | doaj.art-01b060231d4f4c70aa449134a9963c5a2022-12-21T21:17:08ZengBMCJournal of Cheminformatics1758-29462012-03-0141610.1186/1758-2946-4-6Improving integrative searching of systems chemical biology data using semantic annotationChen BinDing YingWild David J<p>Abstract</p> <p>Background</p> <p>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.</p> <p>Results</p> <p>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.</p> <p>Availability</p> <p>Chem2Bio2OWL is available at <url>http://chem2bio2rdf.org/owl</url>. The document is available at <url>http://chem2bio2owl.wikispaces.com</url>.</p>http://www.jcheminf.com/content/4/1/6 |
| spellingShingle | Chen Bin Ding Ying Wild David J Improving integrative searching of systems chemical biology data using semantic annotation Journal of Cheminformatics |
| title | Improving integrative searching of systems chemical biology data using semantic annotation |
| title_full | Improving integrative searching of systems chemical biology data using semantic annotation |
| title_fullStr | Improving integrative searching of systems chemical biology data using semantic annotation |
| title_full_unstemmed | Improving integrative searching of systems chemical biology data using semantic annotation |
| title_short | Improving integrative searching of systems chemical biology data using semantic annotation |
| title_sort | improving integrative searching of systems chemical biology data using semantic annotation |
| url | http://www.jcheminf.com/content/4/1/6 |
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