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Toxicol Appl Pharmacol ; 343: 71-83, 2018 03 15.
Artigo em Inglês | MEDLINE | ID: mdl-29454060

RESUMO

The Adverse Outcome Pathway (AOP) framework describes the progression of a toxicity pathway from molecular perturbation to population-level outcome in a series of measurable, mechanistic responses. The controlled, computer-readable vocabulary that defines an AOP has the ability to, automatically and on a large scale, integrate AOP knowledge with publically available sources of biological high-throughput data and its derived associations. To support the discovery and development of putative (existing) and potential AOPs, we introduce the AOP-DB, an exploratory database resource that aggregates association relationships between genes and their related chemicals, diseases, pathways, species orthology information, ontologies, and gene interactions. These associations are mined from publically available annotation databases and are integrated with the AOP information centralized in the AOP-Wiki, allowing for the automatic characterization of both putative and potential AOPs in the context of multiple areas of biological information, referred to here as "biological entities". The AOP-DB acts as a hypothesis-generation tool for the expansion of putative AOPs, as well as the characterization of potential AOPs, through the creation of association networks across these biological entities. Finally, the AOP-DB provides a useful interface between the AOP framework and existing chemical screening and prioritization efforts by the US Environmental Protection Agency.


Assuntos
Rotas de Resultados Adversos/tendências , Mineração de Dados/métodos , Mineração de Dados/tendências , Bases de Dados Factuais/tendências , Animais , Mineração de Dados/estatística & dados numéricos , Bases de Dados Factuais/estatística & dados numéricos , Efeitos Colaterais e Reações Adversas Relacionados a Medicamentos/genética , Efeitos Colaterais e Reações Adversas Relacionados a Medicamentos/metabolismo , Redes Reguladoras de Genes/efeitos dos fármacos , Redes Reguladoras de Genes/fisiologia , Humanos , Medição de Risco/métodos , Medição de Risco/tendências
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