PANG, Chao, Fleur KELPIN, David VAN ENCKEVORT, Niina EKLUND, Kaisa SILANDER, Dennis HENDRIKSEN, Mark DE HAAN, Jonathan JETTEN, Tommy DE BOER, Bart CHARBON, Petr HOLUB, Hans HILLEGE and Morris A. SWERTZ. BiobankUniverse: automatic matchmaking between datasets for biobank data discovery and integration. Bioinformatics. Oxford: Oxford University Press, 2017, vol. 33, No 22, p. 3627-3634. ISSN 1367-4803. doi:10.1093/bioinformatics/btx478.
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Basic information
Original name BiobankUniverse: automatic matchmaking between datasets for biobank data discovery and integration
Authors PANG, Chao, Fleur KELPIN, David VAN ENCKEVORT, Niina EKLUND, Kaisa SILANDER, Dennis HENDRIKSEN, Mark DE HAAN, Jonathan JETTEN, Tommy DE BOER, Bart CHARBON, Petr HOLUB, Hans HILLEGE and Morris A. SWERTZ.
Edition Bioinformatics, Oxford, Oxford University Press, 2017, 1367-4803.
Other information
Original language English
Type of outcome Article in a journal
Field of Study 10201 Computer sciences, information science, bioinformatics
Country of publisher Canada
Confidentiality degree is not subject to a state or trade secret
WWW DOI
Impact factor Impact factor: 5.481
Doi http://dx.doi.org/10.1093/bioinformatics/btx478
UT WoS 000415074800015
Changed by Changed by: doc. RNDr. Petr Holub, Ph.D., učo 3248. Changed: 29/4/2020 22:10.
Abstract
Biobanks are indispensable for large-scale genetic/epidemiological studies, yet it remains difficult for researchers to determine which biobanks contain data matching their research questions. To overcome this, we developed a new matching algorithm that identifies pairs of related data elements between biobanks and research variables with high precision and recall. It integrates lexical comparison, Unified Medical Language System ontology tagging and semantic query expansion. The result is BiobankUniverse, a fast matchmaking service for biobanks and researchers. Biobankers upload their data elements and researchers their desired study variables, BiobankUniverse automatically shortlists matching attributes between them. Users can quickly explore matching potential and search for biobanks/data elements matching their research. They can also curate matches and define personalized data-universes.
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