Bioassay ontology to describe high-throughput screening assays and their results

Uma Vempati, Ubbo Visser, Saminda Abeyruwan, Kunie Sakurai, Magdalena Przydzial, Caty Chung, Robin Smith, Ainar Koleti, Christopher Mader, Vance Lemmon, Stephan Schürer

Research output: Contribution to journalConference articlepeer-review

1 Scopus citations


Huge amounts of high-throughput screening (HTS) data are generated in the pharmaceutical industry and more recently in the public sector. These are typically analyzed on a per-project basis. Comparison and analysis across many diverse HTS datasets are hindered by the lack of standardized descriptions of biological assays and screening results. Here, we present the BioAssay Ontology (BAO), which enables the categorization of biological assays by concepts relevant to interpret and compare HTS data and thus facilitates data analysis across many HTS campaigns. We used BAO to annotate assays from the largest public HTS data repository. PubChem. Here we demonstrate how BAO can be applied to access and analyze HTS data. BAO makes use of expressive description logic and has potential for discovering implicit knowledge using inference. BAO is publically available from the NCBO BioPortal at http://bioportal.bioontology. org/ontologies/44531.

Original languageEnglish (US)
Pages (from-to)209-216
Number of pages8
JournalCEUR Workshop Proceedings
StatePublished - Dec 1 2011
Event2nd International Conference on Biomedical Ontology, ICBO 2011 - Buffalo, NY, United States
Duration: Jul 26 2011Jul 30 2011


  • Assay ontology
  • Bioassay
  • Bioassay ontology
  • Biological assay
  • Biological screening
  • Data analysis
  • Description logic
  • High-throughput screening
  • HTS
  • Semantic integration

ASJC Scopus subject areas

  • Computer Science(all)


Dive into the research topics of 'Bioassay ontology to describe high-throughput screening assays and their results'. Together they form a unique fingerprint.

Cite this