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Using semantic web rules to reason on an ontology of pseudogenes
Matthew E Holford1, Ekta Khurana, Kei-Hoi Cheung
1Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA. matthew.holford@yale.edu
Motivation:
Recent years have seen the development of a wide range of biomedical ontologies. Notable among these is Sequence Ontology (SO) which offers a rich hierarchy of terms and relationships that can be used to annotate genomic data. Well-designed formal ontologies allow data to be reasoned upon in a consistent and logically sound way and can lead to the discovery of new relationships. The Semantic Web Rules Language (SWRL) augments the capabilities of a reasoner by allowing the creation of conditional rules. To date, however, formal reasoning, especially the use of SWRL rules, has not been widely used in biomedicine.
Results:
We have built a knowledge base of human pseudogenes, extending the existing SO framework to incorporate additional attributes. In particular, we have defined the relationships between pseudogenes and segmental duplications. We then created a series of logical rules using SWRL to answer research questions and to annotate our pseudogenes appropriately. Finally, we were left with a knowledge base which could be queried to discover information about human pseudogene evolution.
Availability:
The fully populated knowledge base described in this document is available for download from http://ontology.pseudogene.org. A SPARQL endpoint from which to query the dataset is also available at this location.
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