Evaluation of QSAR models for the prediction of ames genotoxicity: a retrospective exercise on the chemical substances registered under the EU REACH regulation.
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Innovative Strategies to Develop Chemical Categories Using a Combination of Structural and Toxicological Properties.Fragment Prioritization on a Large Mutagenicity Dataset.Improving confidence in (Q)SAR predictions under Canada's Chemicals Management Plan - a chemical space approach.Origin of the TTC values for compounds that are genotoxic and/or carcinogenic and an approach for their re-evaluation.New clues on carcinogenicity-related substructures derived from mining two large datasets of chemical compounds.ToxRead: a tool to assist in read across and its use to assess mutagenicity of chemicals.Integrating computational methods to predict mutagenicity of aromatic azo compounds.New Quantitative Structure-Activity Relationship Models Improve Predictability of Ames Mutagenicity for Aromatic Azo Compounds.Hierarchical Rules for Read-Across and In Silico Models of Mutagenicity.The Consultancy Activity on In Silico Models for Genotoxic Prediction of Pharmaceutical Impurities.
P2860
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P2860
Evaluation of QSAR models for the prediction of ames genotoxicity: a retrospective exercise on the chemical substances registered under the EU REACH regulation.
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name
Evaluation of QSAR models for ...... under the EU REACH regulation.
@en
Evaluation of QSAR models for ...... under the EU REACH regulation.
@nl
type
label
Evaluation of QSAR models for ...... under the EU REACH regulation.
@en
Evaluation of QSAR models for ...... under the EU REACH regulation.
@nl
prefLabel
Evaluation of QSAR models for ...... under the EU REACH regulation.
@en
Evaluation of QSAR models for ...... under the EU REACH regulation.
@nl
P2093
P2860
P50
P1476
Evaluation of QSAR models for ...... under the EU REACH regulation.
@en
P2093
Alessandra Roncaglioni
Antonio Cassano
Giuseppa Raitano
Josep Cester
P2860
P304
P356
10.1080/10590501.2014.938955
P577
2014-01-01T00:00:00Z