Using semantic web rules to reason on an ontology of pseudogenes. Academic Article uri icon

Overview

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.

publication date

  • June 15, 2010

Research

keywords

  • Information Storage and Retrieval
  • Pseudogenes
  • Semantics

Identity

PubMed Central ID

  • PMC2881358

Scopus Document Identifier

  • 77954195925

Digital Object Identifier (DOI)

  • 10.1093/bioinformatics/btq173

PubMed ID

  • 20529940

Additional Document Info

volume

  • 26

issue

  • 12