Query processing; Bioinformatics; Semantic search; Data integration
Liang Shiqi, Stockinger Kurt, de Farias Tarcisio Mendes, Anisimova Maria, Gil Manuel (2021), Querying knowledge graphs in natural language, in Journal of Big Data
, 8(1), 3.
Mendes de Farias Tarcisio, Stockinger Kurt, Dessimoz Christophe (2019), On the Move to Meaningful Internet Systems: OTM 2019 ConferencesConfederated International Conferences: CoopIS, ODBASE, C&TC 2019, Rhodes, Greece, October 21–25, 2019, Proceedings, in On the Move to Meaningful Internet Systems: OTM 2019 Conferences
, Rhodes, GreeceSpringer International Publishing, Cham.
Sima Ana Claudia, Dessimoz Christophe, Stockinger Kurt, Zahn-Zabal Monique, Mendes de Farias Tarcisio (2019), A hands-on introduction to querying evolutionary relationships across multiple data sources using SPARQL, in F1000Research
, 8, 1822-1822.
Sima Ana Claudia, Stockinger Kurt, de Farias Tarcisio Mendes, Gil Manuel (2019), Evolutionary GenomicsStatistical and Computational Methods
, Springer New York, New York, NY.
Sima Ana Claudia, Mendes de Farias Tarcisio, Zbinden Erich, Anisimova Maria, Gil Manuel, Stockinger Heinz, Stockinger Kurt, Robinson-Rechavi Marc, Dessimoz Christophe (2019), Enabling semantic queries across federated bioinformatics databases, in Database
, 2019, n/a-n/a.
T. M. de Farias et al., Leveraging logical rules for efficacious representation of large orthology datasets, in International Semantic Web Applications and Tools for Healthcare and Life Sciences (SWAT4HCLS)
, Antwerp, Belgum?, Antwerp, Belgum.
One of the major promise of Big Data lies in the simultaneous mining of multiple sources of data. This is particularly important in life sciences, where different and complementary data are scattered across multiple resources. To overcome this issue, the use of RDF/semantic web technology is emerging, but querying these systems often proves to be too complex for most users-thereby hampering wide development and adoption of these technologies. This project aims at enabling sophisticated semantic queries across large, decentralized and heterogeneous databases via an intuitive interface. The system will enable scientists, without prior training, to perform powerful joint queries across resources in ways that cannot be anticipated and therefore goes far beyond the query functionality of specialized knowledge bases.The project represents an interdisciplinary collaboration between information systems and bioinformatics-directly building upon the team’s prior experience in integrating and querying databases at a major Swiss bank, in developing world-leading bioinformatics databases, in combining biological ontologies for data analysis, and in maintaining the highly accessed bioinformatics resource portal ExPASy.