a brief introduction to predictive;
description and representation of chemicals;
computational biology;
toxicological information for use in predictive modeling : quality, sources, and data bases;
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 predictions