Predictive Toxicology

Christoph Helma

• Publisher: CRC Press
• Year: 2005
• eBook ISBN: 9781040212622
• Topic: Medicine
• Subtopic: Environmental Science

A comprehensive overview of techniques and systems currently utilized in predictive toxicology, this reference presents an in-depth survey of strategies, algorithms, and prediction methods to select, calculate, and represent the features and properties of chemical structures in biological systems. It provides sources of high-quality toxicity data, the most important commercial and noncommercial predictive toxicology programs, and advanced technologies in computational chemistry, biology, statistics, and data mining. Predictive Toxicology explores applications that go beyond classical structure-activity relationships and discusses programs such as OncoLogic, META, MC4PC, PASS, and lazar.

Table of contents

• Cover
• Half Title
• Title Page
• Copyright Page
• Contents
• Contributors
• 1 A Brief Introduction to Predictive Toxicology
• 2 Description and Representation of Chemicals
• 3 Computational Biology and Toxicogenomics
• 4 Toxicological Information for Use in Predictive Modeling: Quality, Sources, and Databases
• 5 The Use of Expert Systems for Toxicology Risk Prediction
• 7 Machine Learning and Data Mining
• 8 Neural Networks and Kernel Machines for Vector and Structured Data
• 9 Applications of Substructure-Based SAR in Toxicology
• 10 OncoLogic: A Mechanism-Based Expert System for Predicting the Carcinogenic Potential of Chemicals
• 11 META: An Expert System for the Prediction of Metabolic Transformations
• 12 MC4PC—An Artificial Intelligence Approach to the Discovery of Quantitative Structure-Toxic Activity Relationships
• 13 PASS: Prediction of Biological Activity Spectra for Substances
• 14 lazar: Lazy Structure-Activity Relationships for Toxicity Prediction
• Index