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Aggregating data for computational toxicology applications: The U.S. Environmental Protection Agency (EPA) Aggregated Computational Toxicology Resource (ACToR) System.
Judson, Richard S; Martin, Matthew T; Egeghy, Peter; Gangwal, Sumit; Reif, David M; Kothiya, Parth; Wolf, Maritja; Cathey, Tommy; Transue, Thomas; Smith, Doris; Vail, James; Frame, Alicia; Mosher, Shad; Hubal, Elaine A Cohen; Richard, Ann M.
Afiliação
  • Judson RS; U.S. EPA, National Center for Computational Toxicology, Research Triangle Park, NC 27709, USA.
  • Martin MT; U.S. EPA, National Center for Computational Toxicology, Research Triangle Park, NC 27709, USA.
  • Egeghy P; U.S. EPA, National Exposure Research Laboratory, Research Triangle Park, NC 27709, USA.
  • Gangwal S; U.S. EPA, National Center for Computational Toxicology, Research Triangle Park, NC 27709, USA.
  • Reif DM; U.S. EPA, National Center for Computational Toxicology, Research Triangle Park, NC 27709, USA.
  • Kothiya P; U.S. EPA, National Center for Computational Toxicology, Research Triangle Park, NC 27709, USA.
  • Wolf M; Lockheed Martin, Research Triangle Park, NC, USA.
  • Cathey T; Lockheed Martin, Research Triangle Park, NC, USA.
  • Transue T; Lockheed Martin, Research Triangle Park, NC, USA.
  • Smith D; U.S. EPA, National Center for Computational Toxicology, Research Triangle Park, NC 27709, USA.
  • Vail J; U.S. EPA, National Center for Computational Toxicology, Research Triangle Park, NC 27709, USA.
  • Frame A; U.S. EPA, National Center for Computational Toxicology, Research Triangle Park, NC 27709, USA.
  • Mosher S; U.S. EPA, National Center for Computational Toxicology, Research Triangle Park, NC 27709, USA.
  • Hubal EAC; U.S. EPA, National Center for Computational Toxicology, Research Triangle Park, NC 27709, USA.
  • Richard AM; U.S. EPA, National Center for Computational Toxicology, Research Triangle Park, NC 27709, USA.
Int J Mol Sci ; 13(2): 1805-1831, 2012.
Article em En | MEDLINE | ID: mdl-22408426
Computational toxicology combines data from high-throughput test methods, chemical structure analyses and other biological domains (e.g., genes, proteins, cells, tissues) with the goals of predicting and understanding the underlying mechanistic causes of chemical toxicity and for predicting toxicity of new chemicals and products. A key feature of such approaches is their reliance on knowledge extracted from large collections of data and data sets in computable formats. The U.S. Environmental Protection Agency (EPA) has developed a large data resource called ACToR (Aggregated Computational Toxicology Resource) to support these data-intensive efforts. ACToR comprises four main repositories: core ACToR (chemical identifiers and structures, and summary data on hazard, exposure, use, and other domains), ToxRefDB (Toxicity Reference Database, a compilation of detailed in vivo toxicity data from guideline studies), ExpoCastDB (detailed human exposure data from observational studies of selected chemicals), and ToxCastDB (data from high-throughput screening programs, including links to underlying biological information related to genes and pathways). The EPA DSSTox (Distributed Structure-Searchable Toxicity) program provides expert-reviewed chemical structures and associated information for these and other high-interest public inventories. Overall, the ACToR system contains information on about 400,000 chemicals from 1100 different sources. The entire system is built using open source tools and is freely available to download. This review describes the organization of the data repository and provides selected examples of use cases.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: United States Environmental Protection Agency / Bases de Dados Factuais / Biologia Computacional / Ecotoxicologia Tipo de estudo: Observational_studies / Prognostic_studies Limite: Humans País/Região como assunto: America do norte Idioma: En Revista: Int J Mol Sci Ano de publicação: 2012 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: United States Environmental Protection Agency / Bases de Dados Factuais / Biologia Computacional / Ecotoxicologia Tipo de estudo: Observational_studies / Prognostic_studies Limite: Humans País/Região como assunto: America do norte Idioma: En Revista: Int J Mol Sci Ano de publicação: 2012 Tipo de documento: Article País de afiliação: Estados Unidos