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1.
Int J Mol Sci ; 13(2): 1805-1831, 2012.
Article in English | MEDLINE | ID: mdl-22408426

ABSTRACT

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.


Subject(s)
Computational Biology/methods , Databases, Factual , Ecotoxicology/methods , United States Environmental Protection Agency , Algorithms , Databases, Factual/standards , Databases, Factual/supply & distribution , Ecotoxicology/organization & administration , Environmental Pollutants/toxicity , Humans , Software , United States , United States Environmental Protection Agency/organization & administration
2.
Toxicol Sci ; 109(2): 358-71, 2009 Jun.
Article in English | MEDLINE | ID: mdl-19332651

ABSTRACT

A publicly available toxicogenomics capability for supporting predictive toxicology and meta-analysis depends on availability of gene expression data for chemical treatment scenarios, the ability to locate and aggregate such information by chemical, and broad data coverage within chemical, genomics, and toxicological information domains. This capability also depends on common genomics standards, protocol description, and functional linkages of diverse public Internet data resources. We present a survey of public genomics resources from these vantage points and conclude that, despite progress in many areas, the current state of the majority of public microarray databases is inadequate for supporting these objectives, particularly with regard to chemical indexing. To begin to address these inadequacies, we focus chemical annotation efforts on experimental content contained in the two primary public genomic resources: ArrayExpress and Gene Expression Omnibus. Automated scripts and extensive manual review were employed to transform free-text experiment descriptions into a standardized, chemically indexed inventory of experiments in both resources. These files, which include top-level summary annotations, allow for identification of current chemical-associated experimental content, as well as chemical-exposure-related (or "Treatment") content of greatest potential value to toxicogenomics investigation. With these chemical-index files, it is possible for the first time to assess the breadth and overlap of chemical study space represented in these databases, and to begin to assess the sufficiency of data with shared protocols for chemical similarity inferences. Chemical indexing of public genomics databases is a first important step toward integrating chemical, toxicological and genomics data into predictive toxicology.


Subject(s)
Computational Biology/methods , Toxicogenetics , Toxicology/trends , Database Management Systems , Databases, Factual , Meta-Analysis as Topic , Oligonucleotide Array Sequence Analysis
3.
Bioinformatics ; 25(5): 692-4, 2009 Mar 01.
Article in English | MEDLINE | ID: mdl-19158160

ABSTRACT

SUMMARY: The Distributed Structure-Searchable Toxicity (DSSTox) ARYEXP and GEOGSE files are newly published, structure-annotated files of the chemical-associated and chemical exposure-related summary experimental content contained in the ArrayExpress Repository and Gene Expression Omnibus (GEO) Series (based on data extracted on September 20, 2008). ARYEXP and GEOGSE contain 887 and 1064 unique chemical substances mapped to 1835 and 2381 chemical exposure-related experiment accession IDs, respectively. The standardized files allow one to assess, compare and search the chemical content in each resource, in the context of the larger DSSTox toxicology data network, as well as across large public cheminformatics resources such as PubChem (http://pubchem.ncbi.nlm.nih.gov). AVAILABILITY: Data files and documentation may be accessed online at http://epa.gov/ncct/dsstox/.


Subject(s)
Computational Biology/methods , Databases, Factual , Gene Expression Profiling/methods , Toxicogenetics/methods , Databases, Genetic , Gene Expression , Genomics/methods , Oligonucleotide Array Sequence Analysis/methods , Software
4.
Toxicol Appl Pharmacol ; 233(1): 7-13, 2008 Nov 15.
Article in English | MEDLINE | ID: mdl-18671997

ABSTRACT

ACToR (Aggregated Computational Toxicology Resource) is a database and set of software applications that bring into one central location many types and sources of data on environmental chemicals. Currently, the ACToR chemical database contains information on chemical structure, in vitro bioassays and in vivo toxicology assays derived from more than 150 sources including the U.S. Environmental Protection Agency (EPA), Centers for Disease Control (CDC), U.S. Food and Drug Administration (FDA), National Institutes of Health (NIH), state agencies, corresponding government agencies in Canada, Europe and Japan, universities, the World Health Organization (WHO) and non-governmental organizations (NGOs). At the EPA National Center for Computational Toxicology, ACToR helps manage large data sets being used in a high-throughput environmental chemical screening and prioritization program called ToxCast.


Subject(s)
Computational Biology/methods , Databases, Factual/standards , Environmental Pollutants/toxicity , Computational Biology/standards , Computational Biology/statistics & numerical data , Computational Biology/trends , Databases, Factual/statistics & numerical data , Databases, Factual/trends , Environmental Exposure/adverse effects , Environmental Exposure/standards , Environmental Exposure/statistics & numerical data , Environmental Pollutants/chemistry , Government Agencies/standards , Government Agencies/statistics & numerical data , Government Agencies/trends , United States , United States Environmental Protection Agency/standards , United States Environmental Protection Agency/statistics & numerical data , United States Environmental Protection Agency/trends
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