Predicting compound amenability with liquid chromatography-mass spectrometry to improve non-targeted analysis
The dataset and experimental and predicted amenability calls are provided in the supplemental file “Supplemental_ToxCast_PhaseII.xlsx”.
PaDEL 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 “Supplemental_Application.xlsx”.
It 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 “Supplemental_Application.xlsx” for both ESI+ and ESI-).
Training 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 “Supplemental_train_test.xlsx”.
A list of descriptors is provided in the supplemental file “Supplemental_Descriptors.xlsx”.
A 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 “Supplemental_Figures.docx”.
This dataset is associated with the following publication:
Lowe, 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).
Complete Metadata
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| description | The dataset and experimental and predicted amenability calls are provided in the supplemental file “Supplemental_ToxCast_PhaseII.xlsx”. PaDEL 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 “Supplemental_Application.xlsx”. It 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 “Supplemental_Application.xlsx” for both ESI+ and ESI-). Training 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 “Supplemental_train_test.xlsx”. A list of descriptors is provided in the supplemental file “Supplemental_Descriptors.xlsx”. A 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 “Supplemental_Figures.docx”. This dataset is associated with the following publication: Lowe, 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). |
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| identifier | https://doi.org/10.23719/1524095 |
| keyword |
[
"Predictive Modeling",
"Suspect Screening Analysis",
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| license | https://pasteur.epa.gov/license/sciencehub-license.html |
| modified | 2021-06-03 |
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"name": "U.S. EPA Office of Research and Development (ORD)",
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| 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 |
