Comparison of gene identification based on artificial neural network pre-processing with k-means cluster and principal component analysis

Leif E. Peterson, Matthew A. Coleman

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

10 Scopus citations

Abstract

A combination of gene ranking, dimensional reduction, and recursive feature elimination (RFE) using a BP-MLP artificial neural network (ANN) was used to select genes for DNA microarray classification. Use of k-means cluster analysis for dimensional reduction and maximum sensitivity for RFE resulted in 64-gene models with fewer invariant and correlated features when compared with PCA and mimimum error. In conclusion, k-means cluster analysis and sensitivity may be better suited for classifying diseases for which gene expression is more strongly influenced by pathway heterogeneity.

Original languageEnglish (US)
Title of host publicationFuzzy Logic and Applications - 6th International Workshop, WILF 2005, Revised Selected Papers
PublisherSpringer-Verlag
Pages267-276
Number of pages10
ISBN (Print)3540325298, 9783540325291
DOIs
StatePublished - 2006
Event6th International Workshop - Fuzzy Logic and Applications - Crema, Italy
Duration: Sep 15 2005Sep 17 2005

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3849 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other6th International Workshop - Fuzzy Logic and Applications
CountryItaly
CityCrema
Period9/15/059/17/05

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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