{"accessLevel": "public", "bureauCode": ["020:00"], "contactPoint": {"fn": "Antony Williams", "hasEmail": "mailto:williams.antony@epa.gov"}, "description": "The dataset and experimental and predicted amenability calls are provided in the supplemental file \u201cSupplemental_ToxCast_PhaseII.xlsx\u201d.\n\nPaDEL descriptors were generated for each candidate and amenability predictions were calculated using both ESI+ and ESI- downsampled models.  The resulting dataset is available in the supplemental file \u201cSupplemental_Application.xlsx\u201d.\nIt should be noted that the dataset used in this demonstration is biased toward environmentally relevant chemicals, many of which appear in a large number of chemical lists on the Dashboard (see the DATA_SOURCES column in \u201cSupplemental_Application.xlsx\u201d for both ESI+ and ESI-).  \n\nTraining and test datasets were constructed using the PaDEL descriptors and the ESI+ and ESI- endpoint values discussed previously. These training and test sets are provided in the supplemental file \u201cSupplemental_train_test.xlsx\u201d.\n\nA list of descriptors is provided in the supplemental file \u201cSupplemental_Descriptors.xlsx\u201d.\n\nA similar plot (Figure S1) of variable importance for the ESI+ upsampled model, and a similar plot (Figure S2) of variable importance for the ESI- upsampled model can be found in \u201cSupplemental_Figures.docx\u201d. \n\nThis dataset is associated with the following publication:\nLowe, C., K. Isaacs, A. McEachran, C. Grulke, J. Sobus, E. Ulrich, A. Richard, A. Chao, J. Wambaugh, and A. Williams. Predicting compound amenability with liquid chromatography-mass spectrometry to improve non-targeted analysis.   Analytical and Bioanalytical Chemistry. Springer, New York, NY, USA, 413(30): 7495-7508, (2021).", "distribution": [{"downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1524095/Supplemental_train_test.xlsx", "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet", "title": "Supplemental_train_test.xlsx"}, {"downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1524095/Supplemental_ToxCast_PhaseII.xlsx", "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet", "title": "Supplemental_ToxCast_PhaseII.xlsx"}, {"downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1524095/Supplemental_Descriptors.xlsx", "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet", "title": "Supplemental_Descriptors.xlsx"}, {"downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1524095/Supplemental_Application.xlsx", "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet", "title": "Supplemental_Application.xlsx"}, {"downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1524095/Supplemental_Figures.docx", "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document", "title": "Supplemental_Figures.docx"}], "identifier": "https://doi.org/10.23719/1524095", "keyword": ["non-targeted analysis", "Suspect Screening Analysis", "mass spectrometry", "machine learning", "random forest", "Predictive Modeling"], "license": "https://pasteur.epa.gov/license/sciencehub-license.html", "modified": "2021-06-03", "programCode": ["020:000"], "publisher": {"name": "U.S. EPA Office of Research and Development (ORD)", "subOrganizationOf": {"name": "U.S. Environmental Protection Agency", "subOrganizationOf": {"name": "U.S. Government"}}}, "references": ["https://doi.org/10.1007/s00216-021-03713-w"], "rights": null, "title": "Predicting compound amenability with liquid chromatography-mass spectrometry to improve non-targeted analysis"}