Integrating biological information for feature selection in microarray data classification

Ong Huey Fang, Norwati Mustapha, Md Nasir Sulaiman

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

10 Citations (Scopus)

Abstract

Due to the high dimensionality of microarray data, feature selection is an indispensable task in classification to identify a smaller subset of relevant genes. However, feature selection techniques that consider solely on gene expression values might not be able to identify biologically meaningful genes. Thus, this paper presents an integrative feature selection method that is able to incorporate gene expression data with additional biological data for finding informative genes. The proposed approach is a two-stage method that combined the strength of both filter method and association analysis. The experimental results show that the selected gene subsets are able to improve classification accuracy.

Original languageEnglish
Title of host publication2010 2nd International Conference on Computer Engineering and Applications, ICCEA 2010
Pages330-334
Number of pages5
DOIs
Publication statusPublished - 2010
Externally publishedYes
EventInternational Conference on Computer Engineering and Applications 2010 - Bali Island, Indonesia
Duration: 19 Mar 201021 Mar 2010
Conference number: 2nd
https://ieeexplore.ieee.org/xpl/conhome/5445539/proceeding (Proceedings)

Publication series

Name2010 2nd International Conference on Computer Engineering and Applications, ICCEA 2010
Volume2

Conference

ConferenceInternational Conference on Computer Engineering and Applications 2010
Abbreviated titleICCEA 2010
CountryIndonesia
CityBali Island
Period19/03/1021/03/10
Internet address

Keywords

  • Classification
  • Data mining
  • Feature selection
  • Microarray

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