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AOP-DB: A database resource for the exploration of Adverse Outcome Pathways through integrated association networks.
- Source :
-
Toxicology and applied pharmacology [Toxicol Appl Pharmacol] 2018 Mar 15; Vol. 343, pp. 71-83. Date of Electronic Publication: 2018 Feb 14. - Publication Year :
- 2018
-
Abstract
- 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.<br /> (Published by Elsevier Inc.)
- Subjects :
- Animals
Data Mining statistics & numerical data
Databases, Factual statistics & numerical data
Drug-Related Side Effects and Adverse Reactions genetics
Drug-Related Side Effects and Adverse Reactions metabolism
Gene Regulatory Networks drug effects
Gene Regulatory Networks physiology
Humans
Risk Assessment methods
Risk Assessment trends
Adverse Outcome Pathways trends
Data Mining methods
Data Mining trends
Databases, Factual trends
Subjects
Details
- Language :
- English
- ISSN :
- 1096-0333
- Volume :
- 343
- Database :
- MEDLINE
- Journal :
- Toxicology and applied pharmacology
- Publication Type :
- Academic Journal
- Accession number :
- 29454060
- Full Text :
- https://doi.org/10.1016/j.taap.2018.02.006