Abstract
BackgroundThe biosciences increasingly face the challenge of integrating a wide variety of available data, information and knowledge in order to gain an understanding of biological systems. Data integration is supported by a diverse series of tools, but the lack of a consistent terminology to label these data still presents significant hurdles. As a consequence, much of the available biological data remains disconnected or worse: becomes misconnected. The need to address this terminology problem has spawned the building of a large number of bio-ontologies. OBOF, RDF and OWL are among the most used ontology formats to capture terms and relationships in the Life Sciences, opening the potential to use the Semantic Web to support data integration and further exploitation of integrated resources via automated retrieval and reasoning procedures.MethodsWe extended the Perl suite ONTO-PERL and functionally integrated it into the Galaxy platform. The resulting ONTO-ToolKit supports the analysis and handling of OBO-formatted ontologies via the Galaxy interface, and we demonstrated its functionality in different use cases that illustrate the flexibility to obtain sets of ontology terms that match specific search criteria.ResultsONTO-ToolKit is available as a tool suite for Galaxy. Galaxy not only provides a user friendly interface allowing the interested biologist to manipulate OBO ontologies, it also opens up the possibility to perform further biological (and ontological) analyses by using other tools available within the Galaxy environment. Moreover, it provides tools to translate OBO-formatted ontologies into Semantic Web formats such as RDF and OWL.ConclusionsONTO-ToolKit reaches out to researchers in the biosciences, by providing a user-friendly way to analyse and manipulate ontologies. This type of functionality will become increasingly important given the wealth of information that is becoming available based on ontologies.
Highlights
The biosciences increasingly face the challenge of integrating a wide variety of available data, information and knowledge in order to gain an understanding of biological systems
In use case I we have analysed the relationship between terms from the Cell Cycle Ontology (CCO), an application ontology that we described previously [20]
In use case II we carried out an analysis combining ONTO-ToolKit functionality with other tools available in Galaxy, and in use case III we have demonstrated how a workflow was built to analyse gene sets with Gene Ontology (GO) and S. pombe annotations
Summary
The biosciences increasingly face the challenge of integrating a wide variety of available data, information and knowledge in order to gain an understanding of biological systems. OBOF, RDF and OWL are among the most used ontology formats to capture terms and relationships in the Life Sciences, opening the potential to use the Semantic Web to support data integration and further exploitation of integrated resources via automated retrieval and reasoning procedures. Bio-ontologies have become an important asset for the life sciences They provide a controlled, standard terminology (to support annotations for instance); a variety of tools are available to exploit these ontologies, making them one of the cornerstones for biological data analysis. Automated reasoning, performed on OWL-formatted ontologies via the so-called reasoners (such as HermiT [11]), allows bio-ontologists to perform various tasks such as classification ( known as subsumption), which enables the process of making explicit the relations that were hidden (i.e. implicitly captured), and in general provides help to ensure the consistency of an ontology
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