Using semantic web rules to reason on an ontology of pseudogenes.
BACKGROUND
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.


BACKGROUND
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.
Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA. matthew.holford@yale.edu
Matthew E
ME
Holford
Ekta
E
Khurana
Kei-Hoi
KH
Cheung
Mark
M
Gerstein
D016208:Databases, Factual; D016247:Information Storage and Retrieval / Q000379:methods*; D020407:Internet; D011544:Pseudogenes; D012660:Semantics; D018875:Vocabulary, Controlled