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    • Quantitative Structure-Use Relationship Model Predictions to evaluate Tox21 Chemicals as Functional Substitutes and Candidate Alternatives

    Metadata Updated: November 12, 2020

    This dataset provides a prediction for all Tox21 chemicals with available QSUR descriptors across all 41 valid QSUR models developed with FUse.

    This dataset is associated with the following publication: Phillips, K., J. Wambaugh, C. Grulke, K. Dionisio, and K. Isaacs. High-throughput screening of chemicals as functional substitutes using structure-based classification models. GREEN CHEMISTRY. Royal Society of Chemistry, Cambridge, UK, 19: 1063-1074, (2017).

    Access & Use Information

    Public: This dataset is intended for public access and use. License: See this page for license information.

    Downloads & Resources

    References

    https://doi.org/10.1039/c6gc02744j

    Dates

    Metadata Created Date November 12, 2020
    Metadata Updated Date November 12, 2020

    Metadata Source

    Harvested from EPA ScienceHub

    Other Data Resources

    Additional Metadata

    Resource Type Dataset
    Metadata Created Date November 12, 2020
    Metadata Updated Date November 12, 2020
    Publisher U.S. EPA Office of Research and Development (ORD)
    Maintainer
    Identifier A-wdcg-510
    Data Last Modified 2016-11-30
    Public Access Level public
    Bureau Code 020:00
    Schema Version https://project-open-data.cio.gov/v1.1/schema
    Harvest Object Id b87ae1b5-94cd-4423-af32-d31a46cb5910
    Harvest Source Id 04b59eaf-ae53-4066-93db-80f2ed0df446
    Harvest Source Title EPA ScienceHub
    License https://pasteur.epa.gov/license/sciencehub-license.html
    Program Code 020:095
    Publisher Hierarchy U.S. Government > U.S. Environmental Protection Agency > U.S. EPA Office of Research and Development (ORD)
    Related Documents https://doi.org/10.1039/c6gc02744j
    Source Datajson Identifier True
    Source Hash 1033e09ba8163550e5845ee2a9217fe138299756
    Source Schema Version 1.1

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