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Toxicology Ontology Perspectives
Cambridge Cell Networks.
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2012 (English)In: ALTEX. Alternatives zu Tierexperimenten, ISSN 0946-7785, Vol. 29, no 2, 139-156 p.Article in journal (Refereed) Published
Abstract [en]

The field of predictive toxicology requires the development of open, public, computable, standardized toxicology vocabularies and ontologies to support the applications required by in silico, in vitro, and in vivo toxicology methods and related analysis and reporting activities. In this article we review ontology developments based on a set of perspectives showing how ontologies are being used in predictive toxicology initiatives and applications. Perspectives on resources and initiatives reviewed include OpenTox, eTOX, Pistoia Alliance, ToxWiz, Virtual Liver, EU-ADR, BEL, ToxML, and Bioclipse. We also review existing ontology developments in neighboring fields that can contribute to establishing an ontological framework for predictive toxicology. A significant set of resources is already available to provide a foundation for an ontological framework for 21st century mechanistic-based toxicology research. Ontologies such as ToxWiz provide a basis for application to toxicology investigations, whereas other ontologies under development in the biological, chemical, and biomedical communities could be incorporated in an extended future framework. OpenTox has provided a semantic web framework for the implementation of such ontologies into software applications and linked data resources. Bioclipse developers have shown the benefit of interoperability obtained through ontology by being able to link their workbench application with remote OpenTox web services. Although these developments are promising, an increased international coordination of efforts is greatly needed to develop a more unified, standardized, and open toxicology ontology framework.

Place, publisher, year, edition, pages
2012. Vol. 29, no 2, 139-156 p.
Keyword [en]
toxicology, ontology, framework, data resources, software applications
National Category
Bioinformatics and Systems Biology
Research subject
URN: urn:nbn:se:uu:diva-168657ISI: 000304494900004OAI: oai:DiVA.org:uu-168657DiVA: diva2:501861
Available from: 2012-02-14 Created: 2012-02-14 Last updated: 2015-05-04Bibliographically approved

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Spjuth, Ola
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Department of Pharmaceutical Biosciences
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