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At present, chemical toxicity data resides in a variety of specialized databases, in many different and incompatible formats and in many different locations. Up to now, in order to compile all information on a given chemical, one needed to search multiple databases and then manually compile the resulting data. While this is possible to do for specific chemicals, it is very difficult to compile comprehensive data sets on chemically-similar sets of compounds using structure searching tools. By bringing together data from a large number of sources and making the data structure-searchable, ACToR will facilitate searches that transcend available data and chemical number. As such, it will be an important tool for the advancement of computational toxicology, which requires evaluation of information across broad scales of chemical class, use, structure and biological activity.
The ACToR project is compiling data (both quantitative and qualitative) from a large number of sources (called data collections), including EPA databases, PubChem, other NIH and FDA databases, state and other national sources, and from academic groups. One novel data collection is ToxRefDB, which includes detailed information on in vivo guideline study results for pesticides and other potentially toxic chemicals that has been assembled by the National Center of Computational Toxicology. ACToR is also the primary respository of data being produced by the EPA ToxCast chemical prioritization program.
The majority of chemicals in ACToR have been assigned chemical structures, which will facilitate studies of structure-function relationships in sets of environmental chemicals. The DSSTox Program in the NCCT is responsible for quality structure annotation of chemicals associated with NCCT programs such as ToxRefDB, ToxCast and Tox21. In addition, the full DSSTox structure inventory (approx 12K structures) have been incorporated into ACToR and are the default structure used where available. The majority of the chemical structures within ACToR, however, have been compiled from public sources, such as PubChem, and have varying levels of reliability and accuracy.
Adding new data into ACToR is straightforward. We are always interested in obtaining other data collections that could be incorporated into the system.
ACToR is organized into a series of domains, linked together by chemical.
Chemicals are organized into three main classes, the first two of which are modeled closely after the corresponding PubChem data model
Assays are composed of a set of assay components. These can be quantitative measurements, annotations, or URLs to other sources.
All data is initially compiled as part of a set of Data Collections. A data collection is at minimum a set of substances with corresponding CAS registry numbers and names. Additional information may include chemical structures and assays. As mentioned above, a generic chemical links together data from many data collections on all substances that share a common CAS registry number
In the following summary table, assay results count each substance x assay component x assay combination
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