BioAssay Ontology (BAO): a semantic description of bioassays and high-throughput screening results
Ubbo Visser,Saminda Abeyruwan,Uma D. Vempati,Robin P. Smith,Vance Lemmon,Vance Lemmon,Stephan C. Schürer +6 more
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TLDR
The first ontology to describe HTS experiments and screening results using expressive description logic is developed and BAO opens new functionality for annotating, querying, and analyzing HTS datasets and the potential for discovering new knowledge by means of inference.Abstract:
High-throughput screening (HTS) is one of the main strategies to identify novel entry points for the development of small molecule chemical probes and drugs and is now commonly accessible to public sector research. Large amounts of data generated in HTS campaigns are submitted to public repositories such as PubChem, which is growing at an exponential rate. The diversity and quantity of available HTS assays and screening results pose enormous challenges to organizing, standardizing, integrating, and analyzing the datasets and thus to maximize the scientific and ultimately the public health impact of the huge investments made to implement public sector HTS capabilities. Novel approaches to organize, standardize and access HTS data are required to address these challenges. We developed the first ontology to describe HTS experiments and screening results using expressive description logic. The BioAssay Ontology (BAO) serves as a foundation for the standardization of HTS assays and data and as a semantic knowledge model. In this paper we show important examples of formalizing HTS domain knowledge and we point out the advantages of this approach. The ontology is available online at the NCBO bioportal http://bioportal.bioontology.org/ontologies/44531
. After a large manual curation effort, we loaded BAO-mapped data triples into a RDF database store and used a reasoner in several case studies to demonstrate the benefits of formalized domain knowledge representation in BAO. The examples illustrate semantic querying capabilities where BAO enables the retrieval of inferred search results that are relevant to a given query, but are not explicitly defined. BAO thus opens new functionality for annotating, querying, and analyzing HTS datasets and the potential for discovering new knowledge by means of inference.read more
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The ChEMBL database in 2017.
Anna Gaulton,Anne Hersey,Michal Nowotka,A. Patrícia Bento,Jon Chambers,David Mendez,Prudence Mutowo,Francis Atkinson,Louisa J. Bellis,Elena Cibrian-Uhalte,Mark Davies,Nathan Dedman,Anneli Karlsson,María Paula Magariños,John P. Overington,George Papadatos,Ines Smit,Andrew R. Leach +17 more
TL;DR: ChEMBL is an open large-scale bioactivity database that includes the annotation of assays and targets using ontologies, the inclusion of targets and indications for clinical candidates, addition of metabolic pathways for drugs and calculation of structural alerts.
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The ChEMBL bioactivity database: an update
A. Patrícia Bento,Anna Gaulton,Anne Hersey,Louisa J. Bellis,Jon Chambers,Mark Davies,Felix A. Kruger,Yvonne Light,Lora Mak,Shaun McGlinchey,Michal Nowotka,George Papadatos,Rita Santos,John P. Overington +13 more
TL;DR: More comprehensive tracking of compounds from research stages through clinical development to market is provided through the inclusion of data from United States Adopted Name applications and a new richer data model for representing drug targets has been developed.
Journal ArticleDOI
PubChem BioAssay: 2017 update
Yanli Wang,Stephen H. Bryant,Tiejun Cheng,Jiyao Wang,Asta Gindulyte,Benjamin A. Shoemaker,Paul A. Thiessen,Siqian He,Jian Zhang +8 more
TL;DR: An update for the PubChem Bio Assay database is provided describing several recent development including added sources of research data, redesigned BioAssay record page, new bioAssay classification browser and new features in the Upload system facilitating data sharing.
Journal ArticleDOI
Information retrieval and text mining technologies for chemistry
Martin Krallinger,Obdulia Rabal,Anália Lourenço,Anália Lourenço,Julen Oyarzabal,Alfonso Valencia +5 more
TL;DR: This Review provides a comprehensive and in-depth description of fundamental concepts, technical implementations, and current technologies for meeting information demands of chemical information contained in scientific literature, patents, technical reports, or the web.
Journal ArticleDOI
Perspectives on validation of high-throughput assays supporting 21st century toxicity testing.
Richard S. Judson,Robert J. Kavlock,Matthew T. Martin,David M. Reif,Keith A. Houck,Thomas B. Knudsen,Ann M. Richard,Raymond R. Tice,Maurice Whelan,Menghang Xia,Ruili Huang,Christopher M. Austin,George P. Daston,Thomas Hartung,John R. Fowle,William Wooge,Weida Tong,David J. Dix +17 more
TL;DR: Practical guidelines are discussed that follow current validation practice to the extent possible and practical; make increased use of reference compounds to better demonstrate assay reliability and relevance; and de-emphasize the need for cross-laboratory testing.
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