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The AOP-DB RDF: Applying FAIR Principles to the Semantic Integration of AOP Data Using the Research Description Framework.
Mortensen, Holly M; Martens, Marvin; Senn, Jonathan; Levey, Trevor; Evelo, Chris T; Willighagen, Egon L; Exner, Thomas.
Afiliação
  • Mortensen HM; United States Environmental Protection Agency, Office of Research and Development, Center for Public Health and Environmental Assessment, Research Triangle Park, Durham, NC, United States.
  • Martens M; Department of Bioinformatics (BiGCaT), Maastricht University, Maastricht, Netherlands.
  • Senn J; Oak Ridge Associated Universities, Oak Ridge, TN, United States.
  • Levey T; Oak Ridge Associated Universities, Oak Ridge, TN, United States.
  • Evelo CT; SAS Institute, Cary, NC, United States.
  • Willighagen EL; Department of Bioinformatics (BiGCaT), Maastricht University, Maastricht, Netherlands.
  • Exner T; Maastricht Centre for Systems Biology, Maastricht University, Maastricht, Netherlands.
Front Toxicol ; 4: 803983, 2022.
Article em En | MEDLINE | ID: mdl-35295213
ABSTRACT
Computational toxicology is central to the current transformation occurring in toxicology and chemical risk assessment. There is a need for more efficient use of existing data to characterize human toxicological response data for environmental chemicals in the US and Europe. The Adverse Outcome Pathway (AOP) framework helps to organize existing mechanistic information and contributes to what is currently being described as New Approach Methodologies (NAMs). AOP knowledge and data are currently submitted directly by users and stored in the AOP-Wiki (https//aopwiki.org/). Automatic and systematic parsing of AOP-Wiki data is challenging, so we have created the EPA Adverse Outcome Pathway Database. The AOP-DB, developed by the US EPA to assist in the biological and mechanistic characterization of AOP data, provides a broad, systems-level overview of the biological context of AOPs. Here we describe the recent semantic mapping efforts for the AOP-DB, and how this process facilitates the integration of AOP-DB data with other toxicologically relevant datasets through a use case example.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Front Toxicol Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Front Toxicol Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Estados Unidos