Descriptive mining for the QSAR problem

  • Luminiţa Dumitriu “Dunarea de Jos” University of Galati
  • Marian Crăciun “Dunarea de Jos” University of Galati
  • Cristina Segal “Dunarea de Jos” University of Galati
  • Lucian Georgescu “Dunarea de Jos” University of Galati
Keywords: Quantitative Structure-Activity Relationship, data mining, association rules, classification

Abstract

There are several approaches in trying to solve the Quantitative Structure-Activity (QSAR) problem. These approaches are based either on statistical methods or on predictive data mining using neural networks. Among the statistical methods, one should consider regression analysis, pattern recognition (such as cluster analysis, factor analysis and principal components analysis) or partial least squares. These approaches have a low explanatory capability or non at all. This paper attempts to establish a new approach in solving QSSAR problems using descriptive data mining. This way, the relationship between the chemical properties and the activity of a substance would be comprehensibly modeled.

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Published
2005-10-28
How to Cite
1.
Dumitriu L, Crăciun M, Segal C, Georgescu L. Descriptive mining for the QSAR problem. The Annals of “Dunarea de Jos“ University of Galati. Fascicle III, Electrotechnics, Electronics, Automatic Control, Informatics [Internet]. 28Oct.2005 [cited 23Feb.2025];28:18-2. Available from: https://gup.ugal.ro/ugaljournals/index.php/eeaci/article/view/705
Section
Articles

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