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Leveraging logical rules for efficacious representation of large orthology datasets
Type of publication
Peer-reviewed
Publikationsform
Proceedings (peer-reviewed)
Author
T. M. de Farias et al.,
Project
Bio-SODA: Enabling Complex, Semantic Queries to Bioinformatics Databases through Intuitive Searching over Data
Show all
Proceedings (peer-reviewed)
Title of proceedings
International Semantic Web Applications and Tools for Healthcare and Life Sciences (SWAT4HCLS)
Place
Antwerp, Belgum
Open Access
URL
http://ceur-ws.org/Vol-2042/paper36.pdf
Type of Open Access
Website
Abstract
In the semantic web applied to life sciences, ontologies pro- vide a basis to define concepts and to describe data in biological databases, thereby facilitate data interoperability across multiple resources. In the context of evolutionary genetics, the best corresponding genes across dif- ferent species (e.g. the insulin genes in the pig and the human) are called “orthologs”. Dozens of bioinformatic resources identify and describe such orthologs. To represent the orthology content, an OWL-based orthology ontology (ORTH) was recently proposed. However, ORTH ontology lacks a basis to infer pairwise relations between genes besides more specific and accurate definitions of class restrictions, property domains and property ranges - which is hampering wider adoption by orthology resources. To address this issue, we present in this paper our common efforts to define a release candidate of a second version of ORTH ontology. By using this ontology, we propose a logical rule-based approach to infer information which is not explicitly defined in the primary data. As a benefit of our approach, for example, we can avoid the materialization of several bil- lion triples to represent “is orthologous to” relation when considering the Orthologous Matrix (OMA) dataset.
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