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Internal Test Sets (ITS) Method: a new cross-validation technique to assess the predictive capability of QSAR models. Application to a benchmark set of steroids

A new internal cross-validation method is presented for assessing the true predictive capability of QSAR models. The test is general and can be applied in many QSAR/QSPR approaches. In this work, the method is tested on a well-known benchmark set of steroids. In order to make the calculations, Topological Quantum Similarity Indices and Multiple Linear Regression models were considered

Journal of the Chilean Chemical Society, 2008, vol. 53, núm. 3, p. 1576-1580

Sociedad Chilena de Química

Author: Besalú i Llorà, Emili
Vera, Leonel
Date: 2008
Abstract: A new internal cross-validation method is presented for assessing the true predictive capability of QSAR models. The test is general and can be applied in many QSAR/QSPR approaches. In this work, the method is tested on a well-known benchmark set of steroids. In order to make the calculations, Topological Quantum Similarity Indices and Multiple Linear Regression models were considered
Format: application/pdf
ISSN: 0717-9707
Document access: http://hdl.handle.net/10256/9436
Language: eng
Publisher: Sociedad Chilena de Química
Collection: Reproducció digital del document publicat a: http://www.scielo.cl/pdf/jcchems/v53n3/art05.pdf
Articles publicats (D-Q)
Is part of: Journal of the Chilean Chemical Society, 2008, vol. 53, núm. 3, p. 1576-1580
Rights: Attribution-NonCommercial 3.0 Spain
Rights URI: http://creativecommons.org/licenses/by-nc/3.0/es/
Subject: Química quàntica
Quantum chemistry
QSAR (Bioquímica)
QSAR (Biochemistry)
Title: Internal Test Sets (ITS) Method: a new cross-validation technique to assess the predictive capability of QSAR models. Application to a benchmark set of steroids
Type: info:eu-repo/semantics/article
Repository: DUGiDocs

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