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    • Chromatographic_Retention_Time_Prediction_Models_TALANTA_Data

    Metadata Updated: July 30, 2021

    This paper compares the relative predictive ability and applicability to NTA workflows of three RT prediction models: (1) a logP (octanol-water partition coefficient)-based model using EPI SuiteTM logP predictions; (2) a commercially available ACD/ChromGenius model; and, (3) a newly developed Quantitative Structure Retention Relationship model called OPERA-RT.

    This dataset is associated with the following publication: McEachran, A., K. Mansouri, S. Newton, B. Beverly, J. Sobus, and A. Williams. (TALANTA) A comparison of three liquid chromatography (LC) retention time prediction models. TALANTA. Elsevier Science Ltd, New York, NY, USA, 182: 371-379, (2018).

    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/10.1016/j.talanta.2018.01.022

    Dates

    Metadata Created Date November 12, 2020
    Metadata Updated Date July 30, 2021

    Metadata Source

    Harvested from EPA ScienceHub

    Other Data Resources

    Additional Metadata

    Resource Type Dataset
    Metadata Created Date November 12, 2020
    Metadata Updated Date July 30, 2021
    Publisher U.S. EPA Office of Research and Development (ORD)
    Maintainer
    Identifier https://doi.org/10.23719/1407009
    Data Last Modified 2017-10-03
    Public Access Level public
    Bureau Code 020:00
    Schema Version https://project-open-data.cio.gov/v1.1/schema
    Harvest Object Id 6055d51a-00b3-4dfa-aab0-dde9551b185a
    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/10.1016/j.talanta.2018.01.022
    Source Datajson Identifier True
    Source Hash 9b642c205a199a3403470aff5bfe6a16056838b4
    Source Schema Version 1.1

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