Modelling and prediction of toxicity of environmental pollutants

Frank Lemke, Johann Adolf Müller, Emilio Benfenati

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper describes the problem of modelling toxicity of environmental pollutants using molecular descriptors from a systems theoretical viewpoint. It is shown that current toxicity modelling problems systematically incorporate very high levels of noise a priori. By means of a set of individual and combined models self-organised by KnowledgeMiner from a high-dimensional molecular descriptor data set calculated within the DEMETRA project we suggest a way how results interpretation and final decision making can effectively take into account the huge uncertainty of toxicity models.

Original languageEnglish
Title of host publicationLecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)
EditorsJ.A. Lopez, E. Benfenati, W. Dubitzky
Pages221-234
Number of pages14
Volume3303
Publication statusPublished - 2004
EventInternational Symposium KELSI 2004: Knowledge Exploration in Life Science Informatics - Milan, Italy
Duration: Nov 25 2004Nov 26 2004

Other

OtherInternational Symposium KELSI 2004: Knowledge Exploration in Life Science Informatics
CountryItaly
CityMilan
Period11/25/0411/26/04

ASJC Scopus subject areas

  • Hardware and Architecture
  • Computer Science(all)
  • Theoretical Computer Science

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