Titlebook: Computational Toxicology; Volume II Brad Reisfeld,Arthur N. Mayeno Book 2013 Springer Science+Business Media, LLC 2013 QSAR.biological netw

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Methods for Building QSARsr, the design of such models has many traps for unwary practitioners. Consequently, the purpose of this chapter is to give a practical guide for the computation of SAR and QSAR models, point out problems that may be encountered, and suggest ways of solving them. Attempts are also made to see how these models can be validated and interpreted.

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Methods for Building QSARsy, and pharmacology for predicting the activity of the molecules from their physicochemical properties and/or their structural characteristics. However, the design of such models has many traps for unwary practitioners. Consequently, the purpose of this chapter is to give a practical guide for the c

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Accessing and Using Chemical Databasesproperties. Databases are widely used wherever efficient processing of chemical information is needed, including search, storage, retrieval, and dissemination. Structure and functionality of chemical databases are considered. The typical kinds of information found in a chemical database are consider

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Mutagenicity, Carcinogenicity, and Other End pointsships has seen dramatic progress in the last decades. Coarse-grain, qualitative approaches (e.g., the structural alerts), and fine-tuned quantitative structure–activity relationship models have been developed and used to predict the toxicological properties of untested chemicals. More recently, a nu

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QSAR and Metabolic Assessment Tools in the Assessment of Genotoxicityutational assessment of genotoxicity is illustrated through the application of selected tools to two case-study compounds—2-amino-9H-pyrido[2,3-b]indole (AαC) and 2-aminoacetophenone (2-AAP). The first case study compound (AαC) is an environment pollutant and a food contaminant that can be formed du