Paper Info
Title
Using semantic web rules to reason on an ontology of pseudogenes
Abstract
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. Contact:matthew.holford@yale.edu; mark.gerstein@yale.edu
Year
DOI
Venue
2010
10.1093/bioinformatics/btq173
Bioinformatics [ISMB]
Keywords
Field
DocType
pseudogenes,semantics,internet
Ontology (information science),Ontology,Data mining,Semantic reasoner,Open Biomedical Ontologies,Computer science,Semantic Web,Sequence Ontology,SPARQL,Bioinformatics,Knowledge base
Journal
Volume
Issue
ISSN
26
12
1367-4803
Citations 
PageRank 
References 
11
0.75
10
Authors
4
Name
Order
Citations
PageRank
Matthew Holford1121.10
Ekta Khurana2202.20
Kei-hoi Cheung366460.65
Mark Gerstein435445.41