(Q50086183)

24 February 2018

title

In silico screening of chemicals for bacterial mutagenicity using electrotopological E-state indices and MDL QSAR software (English)

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24 February 2018

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Joseph F Contrera

1

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24 February 2018

Edwin J Matthews

series ordinal

2

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24 February 2018

Naomi L Kruhlak

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3

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24 February 2018

R Daniel Benz

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4

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24 February 2018

language of work or name

English

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publication date

19 October 2005

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24 February 2018

Regulatory Toxicology and Pharmacology

published in

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24 February 2018

volume

43

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24 February 2018

issue

3

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24 February 2018

page(s)

313-323

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24 February 2018

Definitive relationships among chemical structure, carcinogenicity and mutagenicity for 301 chemicals tested by the U.S. NTP

cites work

1 reference

https://api.crossref.org/works/10.1016%2FJ.YRTPH.2005.09.001

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Predicting the carcinogenic potential of pharmaceuticals in rodents using molecular structural similarity and E-state indices

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Considerations in the U.S. Environmental Protection Agency's testing approach for mutagenicity

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A new highly specific method for predicting the carcinogenic potential of pharmaceuticals in rodents using enhanced MCASE QSAR-ES software

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Practical considerations on the use of predictive models for regulatory purposes

7 January 2021

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Three new consensus QSAR models for the prediction of Ames genotoxicity

7 January 2021

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The new chemicals process at the Environmental Protection Agency (EPA): structure-activity relationships for hazard identification and risk assessment

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The prospects for using (Q)SARs in a changing political environment--high expectations and a key role for the european commission's joint research centre

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7 January 2021

Identifiers

DOI

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24 February 2018

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24 February 2018