The Variable Neighborhood Search Metaheuristic for Fuzzy Clustering cDNA Microarray Gene Expression Data

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TypeArticle
ConferenceProceedings of IASTED-AIA-04 Conference, February 16-18, 2004., Innsbruck, Austria
Subjectfuzzy clustering; gene expression; variable neighborhood search metaheuristic; bioinformatics
AbstractSeveral thousand genes can be monitored simultaneously using cDNA microarray technology. To exploit the huge amount of information contained in gene expression data, adaptation of existing and development of new computational methods are required. Recently, the Fuzzy C-Means (F-CM) method has been applied to cluster cDNA microarray data sets. To overcome some shortcomings of F-CM and to improve its performance, it was embedded into a variable neighborhood search (VNS) metaheuristic. The methodology was used to cluster four cDNA microarray data sets. Results show that VNS+F-CM substantially improves the findings obtained by F-CM. This methodology may yield significant benefit in the improvement of decision support systems used for gene expression classification.
Publication date
LanguageEnglish
AffiliationNRC Institute for Information Technology; National Research Council Canada
Peer reviewedNo
NRC number46538
NPARC number8913750
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Record identifier11ffb112-44c9-4254-b692-6f32ba216b1c
Record created2009-04-22
Record modified2016-05-09
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