Regression model (regression) QMRF
Open in:QDB ExplorerQDB Predictor
Name | Type | n |
R2 |
σ |
---|---|---|---|---|
Training set | training | 40 | 0.877 | 0.140 |
Test set | external validation | 20 | 0.904 | 0.106 |
When using this QDB archive, please cite (see details) it together with the original article:
Piir, G. Data for: Development of simple QSPR models for the impact sensitivity of nitramines. QsarDB repository, QDB.231. 2020. https://doi.org/10.15152/QDB.231
Fayet, G.; Rotureau, P. Development of simple QSPR models for the impact sensitivity of nitramines. J. Loss Prev. Process Ind. 2014, 30, 1–8. https://doi.org/10.1016/j.jlp.2014.04.005
Title: | Fayet, G.; Rotureau, P. Development of simple QSPR models for the impact sensitivity of nitramines. J. Loss Prev. Process Ind. 2014, 30, 1–8. |
Abstract: | Quantitative structure–property relationships represent a powerful method alternative to experiments to access the estimation of physico-chemical properties of chemical substances. Such predictions are useful for screening purpose at R&D level. Moreover, this approach is encouraged by the REACH regulation for the collection of data when used cleanly and transparently. The impact sensitivities of 60 nitramine compounds were investigated in a QSPR study following the five principles of validation defined by OECD for the use of models in a regulatory framework. Only constitutional descriptors were employed to achieve QSPR models that could be used without any time consuming preliminary structure calculations at quantum chemical level. To validate models, the original data set was partitioned into a training and validation set. A series of 17 partitions, based on two ratios (40/20 and 45/15) and two division methods (property ranking and random division), were used to achieve this goal. From these partitions, four models exhibiting good predictive power using only constitutional descriptors were highlighted. These models are easier to apply than our previous quantum chemical based model, since they do not need any preliminary calculations. |
URI: | http://hdl.handle.net/10967/231
http://dx.doi.org/10.15152/QDB.231 |
Date: | 2020-04-30 |
Name | Description | Format | Size | View |
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2014JLPPI1.qdb.zip | Model for nitramines | application/zip | 75.55Kb | View/ |
QMRF.pdf | QMRF | 38.78Kb | View/ |