Predictive Toxicology

Predictive Toxicology

Published:
Editor(s):
Free Standard Shipping

Purchasing Options

Hardback
$229.95
Add to cart
ISBN 9780824723972
Cat# DK3038
eBook
ISBN 9780849350351
Cat# DKE5035
 

Features

  • Valuable to readers in a variety of disciplines, this guide provides
  • Demonstrations of various algorithms and their capabilities
  • Methods to select, calculate, and represent the features and properties of chemical structures
  • Applications that go beyond classical structure–activity relationships
  • Discussions of programs such as oncologic, META, MC4PC, PASS, and lazar
  • Reader-friendly glossaries in each chapter
  • Extensive references to introductory and advanced literature
    AUDIENCE
  • Summary

    A comprehensive overview of techniques and systems currently utilized in predictive toxicology, this reference presents an in-depth survey of strategies to characterize chemical structures and biological systems—covering prediction methods and algorithms, sources of high-quality toxicity data, the most important commercial and noncommercial predictive toxicology programs, and advanced technologies in computational chemistry and biology, statistics, and data mining.

    Table of Contents

    A Brief Introduction to Predictive Toxicology. Description and Representation of Chemicals. Computational Biology and Toxicogenomics. Toxicological Information for Use in Predictive Modeling: Quality, Sources, and Databases. The Use of Expert Systems for Toxicology Risk Prediction. Regression- and Projection-Based Approaches in Predictive Toxicology. Machine Learning and Data Mining. Neural Networks and Kernel Machines for Vector and Structured Data. Applications of Substructure-Based SAR in Toxicology. OncoLogic: A Mechanism-Based Expert System for Predicting the Carcinogenic Potential of Chemicals. META: An Expert System for the Prediction of Metabolic Transformations. MC4PC—An Artificial Intelligence Approach to the Discovery of Quantitative Structure-Toxic Activity Relationships. PASS: Prediction of Biological Activity Spectra for Substances. Lazar: Lazy Structure-Activity Relationships for Toxicity Prediction. Index.

    Editorial Reviews

    “… This reference book presents an in-depth survey of strategies to characterize chemical structures and biological systems, covering prediction methods and algorithms, sources of high-quality toxicity data, the most important commercial and non-commercial predictive toxicology programs, and advanced technologies in computational chemistry and biology, statistics, and data mining. … Valuable to readers in a variety of disciplines, such as toxicologists, pharmacologists, computer scientists, statisticians, and researchers in environmental toxicology and drug design, this guide provides demonstrations of various algorithms and their capabilities to select, calculate, and represent the features and properties of chemical structures, demonstrations that og beyond the classical structure-activity relationships.”
    — J Albaigés, Editor in Chief, Department of Environment Chemistry CID-CSIC, Barcelona, Spain, in International Journal Of Environmental Analytical Chemistry, Vol. 86, 2006
    “…provides in-depth reviews of subjects widely considered by workers in this developing field.”
    Toxicology Letters
    “…After using the book, practitioners are likely to have gained a stronger sense of the methodologies behind the techniques….a valuable resource for a field that is quickly developing in practicality.”
    Doody’s Reviews

    Textbooks
    Other CRC Press Sites
    Featured Authors
    STAY CONNECTED
    Facebook Page for CRC Press Twitter Page for CRC Press You Tube Channel for CRC Press LinkedIn Page for CRC Press Google Plus Page for CRC Press
    Sign Up for Email Alerts
    © 2013 Taylor & Francis Group, LLC. All Rights Reserved. Privacy Policy | Cookie Use | Shipping Policy | Contact Us