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Predictive toxicology / edited by Christoph Helma.

Contributor(s): Material type: TextTextPublication details: Boca Raton : Taylor & Francis, 2005Description: x, 508 p. : ill. ; 24 cmISBN:
  • 082472397X (alk. paper)
  • 9780824723972 (hbk)
Subject(s): DDC classification:
  • 615.9 22 C4661
Contents:
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
List(s) this item appears in: Computer_2022
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Item type Current library Call number Status Date due Barcode
Books Books UE-Central Library 615.9 C4661 (Browse shelf(Opens below)) Available T13006

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

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