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In the view of Helma (Institute of Computer Science, U. of Freiburg, Germany), a predictive toxicology system consists of descriptions of chemicals and biological systems as input for predictions, prediction algorithms for processing input information, and toxicity estimations as output data. As such, it is an inherently interdisciplinary enterprise, requiring practitioners in one area of the field to be able to successfully communicate with researchers in other areas. With this in mind, Helma presents 14 chapters introducing the most important techniques and disciplines currently involved in predictive toxicology, including description and representation of chemicals, computational biology, information quality and handling, use of expert systems, machine learning and data mining, neural networks and kernel machines for vector and structured data, and a variety of in-use systems, among other topics. Additional material related to the contents of the book can be found on a companion web site. Annotation c2004 Book News, Inc., Portland, OR (booknews.com)
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