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Gramatica, P.; Pilutti, P.; Papa, E. Approaches for externally validated QSAR modelling of Nitrated Polycyclic Aromatic Hydrocarbon mutagenicity. SAR QSAR Environ. Res. 2007, 18, 169–178.

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Gramatica, P.; Pilutti, P.; Papa, E. Approaches for externally validated QSAR modelling of Nitrated Polycyclic Aromatic Hydrocarbon mutagenicity. SAR QSAR Environ. Res. 2007, 18, 169–178.

QDB archive DOI: 10.15152/QDB.171   DOWNLOAD

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Property logTA100exp: Mutagenicity potency in TA100 without the S9 activation system [log(revertants/nmol)]

Mod4: Full model for mutagenicity of nitrated polycyclic aromatic hydrocarbons

Regression model (regression)

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Name Type n

R2

σ

train training 48 0.814 0.751

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

  • Garcia-Sosa, A. T. Data for: Approaches for externally validated QSAR modelling of Nitrated Polycyclic Aromatic Hydrocarbon mutagenicity. QsarDB repository, QDB.171. 2015. http://dx.doi.org/10.15152/QDB.171

  • Gramatica, P.; Pilutti, P.; Papa, E. Approaches for externally validated QSAR modelling of Nitrated Polycyclic Aromatic Hydrocarbon mutagenicity. SAR QSAR Environ. Res. 2007, 18, 169–178. http://dx.doi.org/10.1080/10629360601054388

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dc.date.accessioned 2015-09-25T08:47:24Z
dc.date.available 2015-09-25T08:47:24Z
dc.date.issued 2015-09-25
dc.identifier.uri http://hdl.handle.net/10967/171
dc.identifier.uri http://dx.doi.org/10.15152/QDB.171
dc.description.abstract Nitrated Polycyclic Aromatic Hydrocarbons (nitro-PAHs), ubiquitous environmental pollutants, are recognized mutagens and carcinogens. A set of mutagenicity data (TA100) for 48 nitro-PAHs was modeled by the Quantitative Structure-Activity Relationships (QSAR) regression method, and OECD principles for QSAR model validation were applied. The proposed Multiple Linear Regression (MLR) models are based on two topological molecular descriptors. The models were validated for predictivity by both internal and external validation. For the external validation, three different splitting approaches, D-optimal Experimental Design, Self Organizing Maps (SOM) and Random Selection by activity sampling, were applied to the original data set in order to compare these methodologies and to select the best descriptors able to model each prediction set chemicals independently of the splitting method applied. The applicability domain was verified by the leverage approach.
dc.publisher Alfonso T. Garcia-Sosa
dc.rights Attribution-ShareAlike 4.0 International
dc.rights.uri http://creativecommons.org/licenses/by-sa/4.0/
dc.title Gramatica, P.; Pilutti, P.; Papa, E. Approaches for externally validated QSAR modelling of Nitrated Polycyclic Aromatic Hydrocarbon mutagenicity. SAR QSAR Environ. Res. 2007, 18, 169–178.
qdb.property.endpoint 4. Human health effects 4.10. Mutagenicity en_US
qdb.property.species Salmonella typhimurium en_US
qdb.descriptor.application DRAGON 5.3 en_US
qdb.prediction.application MOBY DIGS 1.2 en_US
bibtex.entry article en_US
bibtex.entry.author Gramatica, P.
bibtex.entry.author Pilutti, P.
bibtex.entry.author Papa, E.
bibtex.entry.doi 10.1080/10629360601054388 en_US
bibtex.entry.journal SAR QSAR Environ. Res. en_US
bibtex.entry.month jan
bibtex.entry.number 1-2 en_US
bibtex.entry.pages 169–178 en_US
bibtex.entry.title Approaches for externally validated QSAR modelling of Nitrated Polycyclic Aromatic Hydrocarbon mutagenicity en_US
bibtex.entry.volume 18 en_US
bibtex.entry.year 2007
qdb.model.type Regression model (regression) en_US


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  • Publications
    Uni. Insubria (Italy), QSAR Research Unit in Environmental Chemistry and Ecotoxicology

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