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A hands-on introduction to querying evolutionary relationships across multiple data sources using SPARQL

Type of publication Peer-reviewed
Publikationsform Original article (peer-reviewed)
Author Sima Ana Claudia, Dessimoz Christophe, Stockinger Kurt, Zahn-Zabal Monique, Mendes de Farias Tarcisio,
Project Bio-SODA: Enabling Complex, Semantic Queries to Bioinformatics Databases through Intuitive Searching over Data
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Original article (peer-reviewed)

Journal F1000Research
Volume (Issue) 8
Page(s) 1822 - 1822
Title of proceedings F1000Research
DOI 10.12688/f1000research.21027.2

Open Access

Type of Open Access Publisher (Gold Open Access)


The increasing use of Semantic Web technologies in the life sciences, in particular the use of the Resource Description Framework (RDF) and the RDF query language SPARQL, opens the path for novel integrative analyses, combining information from multiple data sources. However, analyzing evolutionary data in RDF is not trivial, due to the steep learning curve required to understand both the data models adopted by different RDF data sources, as well as the equivalent SPARQL constructs required to benefit from this data – in particular, recursive property paths. In this article, we provide a hands-on introduction to querying evolutionary data across several data sources that publish orthology information in RDF, namely: The Orthologous MAtrix (OMA), the European Bioinformatics Institute (EBI) RDF platform, the Database of Orthologous Groups (OrthoDB) and the Microbial Genome Database (MBGD). We present four protocols in increasing order of complexity. In these protocols, we demonstrate through SPARQL queries how to retrieve pairwise orthologs, homologous groups, and hierarchical orthologous groups. Finally, we show how orthology information in different data sources can be compared, through the use of federated SPARQL queries.