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

Bioinformatics. 2017 Nov 15;33(22):3627-3634. doi: 10.1093/bioinformatics/btx478.


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.

Availability and implementation: BiobankUniverse is available at or can be downloaded as part of the open source MOLGENIS suite at


Supplementary information: Supplementary data are available at Bioinformatics online.

MeSH terms

  • Algorithms
  • Computational Biology / methods*
  • Databases, Factual*
  • Software*