• DocumentCode
    3590489
  • Title

    Derivation of quantitative structure-toxicity relationships for ecotoxicological effects of organic chemicals: evolving neural networks and evolving rules

  • Author

    Fogel, Gary B. ; Cheung, Mars

  • Author_Institution
    Natural Selection Inc., La Jolla, CA
  • Volume
    1
  • fYear
    2005
  • Firstpage
    274
  • Abstract
    Organic compounds can produce toxicological effects on aquatic organisms through a variety of mechanisms of action (MOAs). These MOAs can be grouped into two major types: narcotic and reactive. A means to predict MOAs from organic compound structural parameters is important in developing an understanding of environmental toxicity and organism response. This paper presents results of using evolved neural networks or evolved rule-based classifiers to discriminate between narcotic and reactive MOAs of small molecules. The results indicate that both evolutionary methods are useful in this regard
  • Keywords
    data mining; environmental science computing; evolutionary computation; neural nets; organic compounds; pattern classification; toxicology; aquatic organism; ecotoxicological effect; environmental toxicity; evolutionary method; narcotic mechanisms of action; neural network; organic chemical; organic compound; quantitative structure-toxicity relationship; reactive mechanisms of action; rule-based classifier; Biological system modeling; Humans; Neural networks; Optimization methods; Organic chemicals; Organic compounds; Organisms; Predictive models; Testing; Toxicology;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 2005. The 2005 IEEE Congress on
  • Print_ISBN
    0-7803-9363-5
  • Type

    conf

  • DOI
    10.1109/CEC.2005.1554695
  • Filename
    1554695