Endocrine Disruption Modeling

ISBN-13: 9781138111912 / Angielski / Miękka / 2017 / 424 str.

Opis

Based on the research of an international panel of contributors from industry, academia, and regulatory agencies, this book provides an excellent overview of approaches for modeling the endocrine activity of chemicals and the related potential adverse effects they may induce on environmental and human health. It focuses on chemicals accidentally released into the environment and also on the specific design, in agro-chemistry, of chemicals acting on the endocrine system of insects to control them. An interesting feature of the book is the bringing together of these two aspects of endocrine disruption, which are based on the same modeling concepts. It includes a review of available e-resources.

Spis treści

In Silico Methods for Modeling Endocrine Disruption. Mechanisms of Endocrine Disruptions, A Tentative Overview. Population Dynamics Modeling: A Tool For Environmental Risk Assessment of Endocrine Disrupting Chemicals. Application of Pharmacokinetic Modeling to Understand the Mechanism of Action of Endocrine Disrupting Chemicals. Comparative Modeling Review of Nuclear Hormone Receptor Superfamily. The FDA’s Endocrine Disruptor Knowledge Base (EDKB): Lessons Learned in QSAR Modeling and Applications. A Structure-Activity Relationship (SAR) Analysis for the Identification of Environmental Estrogens: The Categorical-SAR (cat-SAR) Approach. Kohonen and Counterpropagation Neural Networks Employed for Modeling Endocrine Disruptors. Quantitative Spectrometric Data-Activity Relationships (QSDAR) Models of Endocrine Disruptor Binding Activities. Mechanism-Based Modeling of Estrogen Receptor Binding Affinity: A COREPA Implementation. Molecular Field Analysis Methods for Modeling Endocrine Disruptors. Structure-Activity Modeling of a Diverse Set of Endrogen Receptor Ligands. SAR and QSAR Analyses of Substituted Dibenzoylhydrazines for Their Mode of Action as Ecdysone Agonists. e-Endocrine Disrupting Chemical Databases for Deriving SAR and QSAR Models.

O autorze

James Devillers