BiobankUniverse: Automatic matchmaking between datasets for biobank data discovery and integration

Chao Pang, 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, Morris A. Swertz*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

2 Citations (Scopus)
275 Downloads (Pure)

Abstract

Motivation: 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.

Results: 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.

Original languageEnglish
Pages (from-to)3627-3634
Number of pages8
JournalBioinformatics
Volume33
Issue number22
DOIs
Publication statusPublished - 15-Nov-2017

Keywords

  • INFORMATION
  • SAMPLES
  • MIABIS

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