A comprehensive fuzzy-based framework for cancer microarray data gene expression analysis

Zhenyu Wang, Vasile Palade

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

19 Citations (Scopus)

Abstract

In this paper, we employ fuzzy techniques for analysing cancer microarray gene expression data. A fuzzy-based ensemble model and a comprehensive fuzzy-based framework for cancer microarray data analysis are being proposed. Our methods were tested on three benchmark microarray cancer data sets, namely Leukemia Cancer Data Set, Colon Cancer Data Set and Lymphoma Cancer Data Set. Comparing to other traditional statistical and machine learning models, the new approach can efficiently tackle several key problems in cancer microarray gene expression data analysis, including highly correlated genes, high dimensionality, highly noisy data and further explanation of the diagnosis results.

Original languageEnglish
Title of host publicationProceedings of the 7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE
PublisherIEEE
Pages1003-1010
Number of pages8
ISBN (Print)1424415098, 9781424415090
DOIs
Publication statusPublished - 2007
Externally publishedYes
Event7th IEEE International Conference on Bioinformatics and Bioengineering - Boston, United States
Duration: 14 Jan 200717 Jan 2007

Conference

Conference7th IEEE International Conference on Bioinformatics and Bioengineering
Abbreviated titleBIBE
CountryUnited States
CityBoston
Period14/01/0717/01/07

ASJC Scopus subject areas

  • Biotechnology
  • Genetics
  • Bioengineering

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