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Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-18771
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dc.contributor.authorSima, Ana-Claudia-
dc.contributor.authorMendes de Farias, Tarcisio-
dc.contributor.authorZbinden, Erich-
dc.contributor.authorAnisimova, Maria-
dc.contributor.authorGil, Manuel-
dc.contributor.authorStockinger, Heinz-
dc.contributor.authorStockinger, Kurt-
dc.contributor.authorRobinson-Rechavi, Marc-
dc.contributor.authorDessimoz, Christophe-
dc.date.accessioned2019-11-29T14:11:07Z-
dc.date.available2019-11-29T14:11:07Z-
dc.date.issued2019-
dc.identifier.issn1758-0463de_CH
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/18771-
dc.description.abstractMotivation: Data integration promises to be one of the main catalysts in enabling new insights to be drawn from the wealth of biological data available publicly. However, the heterogeneity of the different data sources, both at the syntactic and the semantic level, still poses significant challenges for achieving interoperability among biological databases. Results: We introduce an ontology-based federated approach for data integration. We applied this approach to three heterogeneous data stores that span different areas of biological knowledge: (i) Bgee, a gene expression relational database; (ii) Orthologous Matrix (OMA), a Hierarchical Data Format 5 orthology DS; and (iii) UniProtKB, a Resource Description Framework (RDF) store containing protein sequence and functional information. To enable federated queries across these sources, we first defined a new semantic model for gene expression called GenEx. We then show how the relational data in Bgee can be expressed as a virtual RDF graph, instantiating GenEx, through dedicated relational-to-RDF mappings. By applying these mappings, Bgee data are now accessible through a public SPARQL endpoint. Similarly, the materialized RDF data of OMA, expressed in terms of the Orthology ontology, is made available in a public SPARQL endpoint. We identified and formally described intersection points (i.e. virtual links) among the three data sources. These allow performing joint queries across the data stores. Finally, we lay the groundwork to enable nontechnical users to benefit from the integrated data, by providing a natural language template-based search interface.de_CH
dc.language.isoende_CH
dc.publisherOxford University Pressde_CH
dc.relation.ispartofDatabase: The Journal of Biological Databases and Curationde_CH
dc.rightshttp://creativecommons.org/licenses/by/4.0/de_CH
dc.subjectSemantic queryde_CH
dc.subjectFederated databasede_CH
dc.subjectSemantic web technologyde_CH
dc.subjectData integrationde_CH
dc.subjectQuery processingde_CH
dc.subjectNatural language interfacede_CH
dc.subject.ddc005: Computerprogrammierung, Programme und Datende_CH
dc.titleEnabling semantic queries across federated bioinformatics databasesde_CH
dc.typeBeitrag in wissenschaftlicher Zeitschriftde_CH
dcterms.typeTextde_CH
zhaw.departementLife Sciences und Facility Managementde_CH
zhaw.departementSchool of Engineeringde_CH
zhaw.organisationalunitInstitut für Informatik (InIT)de_CH
zhaw.organisationalunitInstitut für Computational Life Sciences (ICLS)de_CH
dc.identifier.doi10.1093/database/baz106de_CH
dc.identifier.doi10.21256/zhaw-18771-
dc.identifier.pmid31697362de_CH
zhaw.funding.euNode_CH
zhaw.issuebaz106de_CH
zhaw.originated.zhawYesde_CH
zhaw.publication.statuspublishedVersionde_CH
zhaw.volume2019de_CH
zhaw.publication.reviewPeer review (Publikation)de_CH
zhaw.funding.snf167149de_CH
zhaw.webfeedApplied Mathematical Biologyde_CH
zhaw.webfeedComputational Genomicsde_CH
zhaw.webfeedData Management & Visualisationde_CH
zhaw.webfeedDatalabde_CH
zhaw.webfeedInformation Engineeringde_CH
zhaw.funding.zhawBio-SODA: Enabling Complex, Semantic Queries to Bioinformatics Databases through Intuitive Searching over Datade_CH
zhaw.author.additionalNode_CH
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Sima, A.-C., Mendes de Farias, T., Zbinden, E., Anisimova, M., Gil, M., Stockinger, H., Stockinger, K., Robinson-Rechavi, M., & Dessimoz, C. (2019). Enabling semantic queries across federated bioinformatics databases. Database: The Journal of Biological Databases and Curation, 2019(baz106). https://doi.org/10.1093/database/baz106
Sima, A.-C. et al. (2019) ‘Enabling semantic queries across federated bioinformatics databases’, Database: The Journal of Biological Databases and Curation, 2019(baz106). Available at: https://doi.org/10.1093/database/baz106.
A.-C. Sima et al., “Enabling semantic queries across federated bioinformatics databases,” Database: The Journal of Biological Databases and Curation, vol. 2019, no. baz106, 2019, doi: 10.1093/database/baz106.
SIMA, Ana-Claudia, Tarcisio MENDES DE FARIAS, Erich ZBINDEN, Maria ANISIMOVA, Manuel GIL, Heinz STOCKINGER, Kurt STOCKINGER, Marc ROBINSON-RECHAVI und Christophe DESSIMOZ, 2019. Enabling semantic queries across federated bioinformatics databases. Database: The Journal of Biological Databases and Curation. 2019. Bd. 2019, Nr. baz106. DOI 10.1093/database/baz106
Sima, Ana-Claudia, Tarcisio Mendes de Farias, Erich Zbinden, Maria Anisimova, Manuel Gil, Heinz Stockinger, Kurt Stockinger, Marc Robinson-Rechavi, and Christophe Dessimoz. 2019. “Enabling Semantic Queries across Federated Bioinformatics Databases.” Database: The Journal of Biological Databases and Curation 2019 (baz106). https://doi.org/10.1093/database/baz106.
Sima, Ana-Claudia, et al. “Enabling Semantic Queries across Federated Bioinformatics Databases.” Database: The Journal of Biological Databases and Curation, vol. 2019, no. baz106, 2019, https://doi.org/10.1093/database/baz106.


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