OntoSNP: Ontology driven knowledgebase for SNP

Abstract

Ontology-based knowledgebase system can provide great benefits for analysis of biological information. Currently, some ontology-driven information systems have been introduced in this filed. In most cases, however, the advantage of ontology which computer science technology can provide is not fully implemented. Even the well-known ontologies such as Gene Ontology (GO) include only limited number of properties for each term. To find meaningful information across complex relation chains among data, indispensable properties of each term should be described and relationship among data can be analyzed by reasoning. Ontology with rules can play a key role in bioinformatics area because, as well as interoperability, it finds new knowledge and checks validity of candidate knowledge automatically using a reasoning engine. In this paper, we propose an ontology-based information system for SNP analysis (OntoSNP) equipped with Web Ontology Language (OWL) and a reasoning engine. The proposed system provides finding of SNP-gene-disease relations, automatic data validity and knowledge conflict checking. OntoSNP is based on well-defined SNP-gene-disease ontology model in OWL and knowledge-finding and validation rules in Semantic Web Rule Language (SWRL).