Regression model (regression) QMRF
Open in:QDB ExplorerQDB Predictor
Name | Type | n |
R2 |
σ |
---|---|---|---|---|
Training set | training | 449 | 0.750 | 0.627 |
Regression model (regression) QMRF
Open in:QDB ExplorerQDB Predictor
Name | Type | n |
R2 |
σ |
---|---|---|---|---|
Training set | training | 643 | 0.794 | 0.543 |
Regression model (regression) QMRF
Open in:QDB ExplorerQDB Predictor
Name | Type | n |
R2 |
σ |
---|---|---|---|---|
Training set | training | 250 | 0.848 | 0.688 |
Regression model (regression) QMRF
Open in:QDB ExplorerQDB Predictor
Name | Type | n |
R2 |
σ |
---|---|---|---|---|
Training set | training | 129 | 0.759 | 0.876 |
Regression model (regression)
Open in:QDB ExplorerQDB Predictor
Name | Type | n |
R2 |
σ |
---|---|---|---|---|
Training set | training | 632 | 0.749 | 0.581 |
Regression model (regression) QMRF
Open in:QDB ExplorerQDB Predictor
Name | Type | n |
R2 |
σ |
---|---|---|---|---|
Training set | training | 30 | 0.883 | 0.262 |
Regression model (regression) QMRF
Open in:QDB ExplorerQDB Predictor
Name | Type | n |
R2 |
σ |
---|---|---|---|---|
Training set | training | 29 | 0.863 | 0.394 |
Regression model (regression) QMRF
Open in:QDB ExplorerQDB Predictor
Name | Type | n |
R2 |
σ |
---|---|---|---|---|
Training set | training | 48 | 0.828 | 0.719 |
Regression model (regression) QMRF
Open in:QDB ExplorerQDB Predictor
Name | Type | n |
R2 |
σ |
---|---|---|---|---|
Training set | training | 30 | 0.967 | 0.258 |
Regression model (regression) QMRF
Open in:QDB ExplorerQDB Predictor
Name | Type | n |
R2 |
σ |
---|---|---|---|---|
Training set | training | 25 | 0.815 | 20.993 |
Regression model (regression) QMRF
Open in:QDB ExplorerQDB Predictor
Name | Type | n |
R2 |
σ |
---|---|---|---|---|
Training set | training | 34 | 0.985 | 0.171 |
Regression model (regression) QMRF
Open in:QDB ExplorerQDB Predictor
Name | Type | n |
R2 |
σ |
---|---|---|---|---|
Training set | training | 56 | 0.786 | 0.711 |
Regression model (regression) QMRF
Open in:QDB ExplorerQDB Predictor
Name | Type | n |
R2 |
σ |
---|---|---|---|---|
Training set | training | 52 | 0.787 | 0.785 |
Regression model (regression) QMRF
Open in:QDB ExplorerQDB Predictor
Name | Type | n |
R2 |
σ |
---|---|---|---|---|
Training set | training | 50 | 0.890 | 0.410 |
Regression model (regression) QMRF
Open in:QDB ExplorerQDB Predictor
Name | Type | n |
R2 |
σ |
---|---|---|---|---|
Training set | training | 20 | 0.851 | 0.686 |
Regression model (regression) QMRF
Open in:QDB ExplorerQDB Predictor
Name | Type | n |
R2 |
σ |
---|---|---|---|---|
Training set | training | 35 | 0.931 | 0.733 |
Regression model (regression) QMRF
Open in:QDB ExplorerQDB Predictor
Name | Type | n |
R2 |
σ |
---|---|---|---|---|
Training set | training | 64 | 0.859 | 0.665 |
Regression model (regression) QMRF
Open in:QDB ExplorerQDB Predictor
Name | Type | n |
R2 |
σ |
---|---|---|---|---|
Training set | training | 56 | 0.810 | 27.386 |
Regression model (regression) QMRF
Open in:QDB ExplorerQDB Predictor
Name | Type | n |
R2 |
σ |
---|---|---|---|---|
Training set | training | 49 | 0.831 | 0.512 |
Regression model (regression) QMRF
Open in:QDB ExplorerQDB Predictor
Name | Type | n |
R2 |
σ |
---|---|---|---|---|
Training set | training | 33 | 0.798 | 0.801 |
Regression model (regression) QMRF
Open in:QDB ExplorerQDB Predictor
Name | Type | n |
R2 |
σ |
---|---|---|---|---|
Training set | training | 35 | 0.821 | 0.425 |
Regression model (regression) QMRF
Open in:QDB ExplorerQDB Predictor
Name | Type | n |
R2 |
σ |
---|---|---|---|---|
Training set | training | 97 | 0.729 | 0.420 |
Regression model (regression) QMRF
Open in:QDB ExplorerQDB Predictor
Name | Type | n |
R2 |
σ |
---|---|---|---|---|
Training set | training | 75 | 0.759 | 0.518 |
When using this QDB archive, please cite (see details) it together with the original article:
Piir, G. Data for: QSARINS-chem: Insubria datasets and new QSAR/QSPR models for environmental pollutants in QSARINS. QsarDB repository, QDB.177. 2016. https://doi.org/10.15152/QDB.177
Gramatica, P.; Cassani, S.; Chirico, N. QSARINS-chem: Insubria datasets and new QSAR/QSPR models for environmental pollutants in QSARINS. J. Comput. Chem. 2014, 35, 1036–1044. https://doi.org/10.1002/jcc.23576
Title: | Gramatica, P.; Cassani, S.; Chirico, N. QSARINS-chem: Insubria datasets and new QSAR/QSPR models for environmental pollutants in QSARINS. J. Comput. Chem. 2014, 35, 1036–1044. |
Abstract: | A database of environmentally hazardous chemicals, collected and modeled by QSAR by the Insubria group, is included in the updated version of QSARINS, software recently proposed for the development and validation of QSAR models by the genetic algorithm-ordinary least squares method. In this version, a module, named QSARINS-Chem, includes several datasets of chemical structures and their corresponding endpoints (physicochemical properties and biological activities). The chemicals are accessible in different ways (CAS, SMILES, names and so forth) and their three-dimensional structure can be visualized. Some of the QSAR models, previously published by our group, have been redeveloped using the free online software for molecular descriptor calculation, PaDEL-Descriptor. The new models can be easily applied for future predictions on chemicals without experimental data, also verifying the applicability domain to new chemicals. The QSAR model reporting format (QMRF) of these models is also here downloadable. Additional chemometric analyses can be done by principal component analysis and multicriteria decision making for screening and ranking chemicals to prioritize the most dangerous. |
URI: | http://hdl.handle.net/10967/177
http://dx.doi.org/10.15152/QDB.177 |
Date: | 2016-02-26 |
Name | Description | Format | Size | View |
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2014JCC1036.qdb.zip | Models from QSARINS software | application/zip | 605.2Kb | View/ |
Q15-33-0013.pdf | QMRF | 44.82Kb | View/ |
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Q17-26-0032.pdf | QMRF | 45.82Kb | View/ |
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Q15-66-0018.pdf | QMRF | 45.28Kb | View/ |
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Q15-41-0014.pdf | QMRF | 43.53Kb | View/ |
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Q15-32-0015.pdf | QMRF | 44.74Kb | View/ |
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Q15-31-0011.pdf | QMRF | 45.17Kb | View/ |
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Q15-33-0012.pdf | QMRF | 45.25Kb | View/ |
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Tab2.Model_4.pdf | QMRF | 50.80Kb | View/ |
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Tab2.Model_6.pdf | QMRF | 49.19Kb | View/ |
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Tab2.Model_7.pdf | QMRF | 50.49Kb | View/ |
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Tab2.Model_8.pdf | QMRF | 51.56Kb | View/ |
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Tab2.Model_9.pdf | QMRF | 50.76Kb | View/ |
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Tab2.Model_10.pdf | QMRF | 50.61Kb | View/ |
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Tab2.Model_11.pdf | QMRF | 50.78Kb | View/ |
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Tab2.Model_13.pdf | QMRF | 52.66Kb | View/ |
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Tab2.Model_14.pdf | QMRF | 53.11Kb | View/ |
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Tab2.Model_15.pdf | QMRF | 52.33Kb | View/ |
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Tab2.Model_16.pdf | QMRF | 51.95Kb | View/ |
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Tab2.Model_17.pdf | QMRF | 52.13Kb | View/ |
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Tab2.Model_18.pdf | QMRF | 52.70Kb | View/ |
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Tab2.Model_19.pdf | QMRF | 50.79Kb | View/ |
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Tab2.Model_20.pdf | QMRF | 49.66Kb | View/ |