Gramatica, P.; Chirico, N.; Papa, E.; Cassani, S.; Kovarich, S. QSARINS: A new software for the development, analysis, and validation of QSAR MLR models. Journal of Computational Chemistry 2013, 34, 2121–2132.

QsarDB Repository

Gramatica, P.; Chirico, N.; Papa, E.; Cassani, S.; Kovarich, S. QSARINS: A new software for the development, analysis, and validation of QSAR MLR models. Journal of Computational Chemistry 2013, 34, 2121–2132.

QDB archive DOI: 10.15152/QDB.181   DOWNLOAD

QsarDB content

Property PBT_Index: PBT Index i

Eq1: Full model i

Regression model (regression)   QMRF

Open in:QDB ExplorerQDB Predictor

NameTypen

R2

σ

Training settraining1800.8890.507
Eq2: Split model i

Regression model (regression)   QMRF

Open in:QDB ExplorerQDB Predictor

NameTypen

R2

σ

Training set itraining920.8890.521
Validation setexternal validation880.8880.498

Citing

When using this QDB archive, please cite (see details) it together with the original article:

  • Kahn, I. Data for: QSARINS: A new software for the development, analysis, and validation of QSAR MLR models. QsarDB repository, QDB.181. 2016. http://dx.doi.org/10.15152/QDB.181

  • Gramatica, P.; Chirico, N.; Papa, E.; Cassani, S.; Kovarich, S. QSARINS: A new software for the development, analysis, and validation of QSAR MLR models. J. Comput. Chem. 2013, 34, 2121–2132. http://dx.doi.org/10.1002/jcc.23361

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Title: Gramatica, P.; Chirico, N.; Papa, E.; Cassani, S.; Kovarich, S. QSARINS: A new software for the development, analysis, and validation of QSAR MLR models. Journal of Computational Chemistry 2013, 34, 2121–2132.
Abstract:QSARINS (QSAR-INSUBRIA) is a new software for the development and validation of multiple linear regression Quantitative Structure-Activity Relationship (QSAR) models by Ordinary Least Squares method and Genetic Algorithm for variable selection. This program is mainly focused on the external validation of QSAR models. Various tools for explorative analysis of the datasets by Principal Component Analysis, prereduction of input molecular descriptors, splitting of datasets in training and prediction sets, detection of outliers and interpolated or extrapolated predictions, internal and external validation by different parameters, consensus modeling and various plots for visualizations are implemented. QSARINS is a user-friendly platform for QSAR modeling in agreement with the OECD Principles and for the analysis of the reliability of the obtained predicted data. The Insubria Persistent Bioaccumulative and Toxic (PBT) Index model for the prediction of the cumulative behavior of new chemicals as PBTs is implemented. Additionally, QSARINS allows the user to validate single models, predeveloped using also different software.
URI:http://hdl.handle.net/10967/181
http://dx.doi.org/10.15152/QDB.181
Date:2016-08-22


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