Description

Book Synopsis

Uses Computational Tools to Simulate Endocrine Disruption Phenomena

Endocrine Disruption Modeling provides a practical overview of the current approaches for modeling endocrine activity and the related potential adverse effects they may induce on environmental and human health. Based on the extensive research of an international panel of contributors from industry, academia, and regulatory agencies, this is the first book devoted to using computer tools to better understand and simulate the multifaceted aspects of endocrine disruption in humans and wildlife.

Explores Diverse Modeling Techniques and Applications

This up-to-date resource focuses on xenobiotics that are accidentally released into the environment with the potential to disturb the normal functioning of the endocrine system of invertebrates and vertebrates but also on the specific agro-chemistry design of chemicals that take control

Table of Contents

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.

Endocrine Disruption Modeling

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    A Hardback by James Devillers

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      Publisher: Taylor & Francis Inc
      Publication Date: Publication Date: 27/04/2009
      ISBN13: 9781420076356, 978-1420076356
      ISBN10: 1420076353

      Description

      Book Synopsis

      Uses Computational Tools to Simulate Endocrine Disruption Phenomena

      Endocrine Disruption Modeling provides a practical overview of the current approaches for modeling endocrine activity and the related potential adverse effects they may induce on environmental and human health. Based on the extensive research of an international panel of contributors from industry, academia, and regulatory agencies, this is the first book devoted to using computer tools to better understand and simulate the multifaceted aspects of endocrine disruption in humans and wildlife.

      Explores Diverse Modeling Techniques and Applications

      This up-to-date resource focuses on xenobiotics that are accidentally released into the environment with the potential to disturb the normal functioning of the endocrine system of invertebrates and vertebrates but also on the specific agro-chemistry design of chemicals that take control

      Table of Contents

      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.

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