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Publication type: Article in scientific journal
Type of review: Open peer review
Title: A hands-on introduction to querying evolutionary relationships across multiple data sources using SPARQL
Authors: Sima, Ana-Claudia
Dessimoz, Christophe
Stockinger, Kurt
Zahn-Zabal, Monique
Mendes de Farias, Tarcisio
et. al: No
DOI: 10.12688/f1000research.21027.2
Published in: F1000Research
Volume(Issue): 8
Page(s): 1822
Issue Date: Aug-2020
Publisher / Ed. Institution: Faculty of 1000
ISSN: 2046-1402
Language: English
Subjects: Comparative Genomics; Orthology; Resource Description Framework (RDF); SPARQL; Sequence Homology
Subject (DDC): 005: Computer programming, programs and data
Abstract: 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.
Fulltext version: Published version
License (according to publishing contract): CC BY 4.0: Attribution 4.0 International
Departement: School of Engineering
Organisational Unit: Institute of Applied Information Technology (InIT)
Published as part of the ZHAW project: SNF NRP 75 "Big Data": Bio-SODA - Enabling Complex, Semantic Queries to Bioinformatics Databases through Intuitive Searching over Data
Appears in collections:Publikationen School of Engineering

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