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An examination of data quality on QSAR Modeling in regards to the environmental sciences (UNC-CH talk)
Williams, A. AND K. Mansouri. An examination of data quality on QSAR Modeling in regards to the environmental sciences (UNC-CH talk). Presented at UNC-CH Talk, Chapel Hill, NC, April 12, 2016. https://doi.org/10.23645/epacomptox.5063236
presentation at UNC-CH.
The development of QSAR models is critically dependent on the quality of available data. As part of our efforts to develop public platforms to provide access to predictive models, we have attempted to discriminate the influence of the quality versus quantity of data available to develop and validate QSAR models. We have focused our efforts on the widely used EPISuite software that was initially developed over two decades ago and, specifically, on the PHYSPROP dataset used to train the EPISuite prediction models. This presentation will review our approaches to examining key datasets, the delivery of curated data and the development of machine-learning models for thirteen separate property endpoints of interest to environmental science. We will also review how these data will be made freely accessible to the community via a new “chemistry dashboard”. This abstract does not reflect U.S. EPA policy.
DASHBOARD AND EPISUITE_KM_FINAL.PDF (PDF,NA pp, 2079.431 KB, about PDF)
Record Details:Record Type: DOCUMENT (PRESENTATION/SLIDE)
Organization:U.S. ENVIRONMENTAL PROTECTION AGENCY
OFFICE OF RESEARCH AND DEVELOPMENT
NATIONAL CENTER FOR COMPUTATIONAL TOXICOLOGY