Abstract
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 language | English (US) |
|---|---|
| Title of host publication | CEUR Workshop Proceedings |
| Pages | 209-216 |
| Number of pages | 8 |
| Volume | 833 |
| State | Published - 2011 |
| Event | 2nd International Conference on Biomedical Ontology, ICBO 2011 - Buffalo, NY, United States Duration: Jul 26 2011 → Jul 30 2011 |
Other
| Other | 2nd International Conference on Biomedical Ontology, ICBO 2011 |
|---|---|
| Country | United States |
| City | Buffalo, NY |
| Period | 7/26/11 → 7/30/11 |
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Keywords
- 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)
Cite this
Bioassay ontology to describe high-throughput screening assays and their results. / Vempati, Uma; Visser, Ubbo E; Abeyruwan, Saminda; Sakurai, Kunie; Przydzial, Magdalena; Chung, Caty; Smith, Robin; Koleti, Ainar; Mader, Christopher; Lemmon, Vance; Schuerer, Stephan C.
CEUR Workshop Proceedings. Vol. 833 2011. p. 209-216.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Bioassay ontology to describe high-throughput screening assays and their results
AU - Vempati, Uma
AU - Visser, Ubbo E
AU - Abeyruwan, Saminda
AU - Sakurai, Kunie
AU - Przydzial, Magdalena
AU - Chung, Caty
AU - Smith, Robin
AU - Koleti, Ainar
AU - Mader, Christopher
AU - Lemmon, Vance
AU - Schuerer, Stephan C
PY - 2011
Y1 - 2011
N2 - 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.
AB - 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.
KW - Assay ontology
KW - Bioassay
KW - Bioassay ontology
KW - Biological assay
KW - Biological screening
KW - Data analysis
KW - Description logic
KW - High-throughput screening
KW - HTS
KW - Semantic integration
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UR - http://www.scopus.com/inward/citedby.url?scp=84891939872&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:84891939872
VL - 833
SP - 209
EP - 216
BT - CEUR Workshop Proceedings
ER -