Fuzzy J-Means and VNS Methods for Clustering Genes from Microarray Data

Download
  1. (PDF, 1 MB)
  2. Get@NRC: Fuzzy J-Means and VNS Methods for Clustering Genes from Microarray Data (Opens in a new window)
DOIResolve DOI: http://doi.org/10.1093/bioinformatics/bth142
AuthorSearch for: ; Search for: ; Search for: ; Search for:
TypeArticle
Journal titleBioinformatics
Volume20
Issue11
Pages16901701; # of pages: 12
AbstractMotivation: In the interpretation of gene expression data from a group of microarray experiments that include samples from either different patients or conditions, special consideration must be given to the pleiotropic and epistatic roles of genes, as observed in the variation of gene co-expression patterns. Crisp clustering methods assign each gene to one cluster, thereby omitting information about the multiple roles of genes.Results: Here we present the application of a local search heuristic, Fuzzy J-Means, embedded into the Variable Neighborhood Search metaheuristic for the clustering of microarray gene expression data. We show that for all data sets studied this algorithm outperforms the standard Fuzzy C-Means heuristic. Different methods for the utilization of cluster membership information in determining gene co-regulation are presented. The clustering and data analyses were performed on simulated data sets as well as experimental cDNA microarray data for breast cancer and human blood from the Stanford Microarray Database.
Publication date
LanguageEnglish
AffiliationNRC Institute for Information Technology; National Research Council Canada
Peer reviewedNo
NRC number46546
NPARC number8913318
Export citationExport as RIS
Report a correctionReport a correction
Record identifier522d0b0d-745b-4f18-bab6-e7045e3ddda2
Record created2009-04-22
Record modified2016-05-09
Bookmark and share
  • Share this page with Facebook (Opens in a new window)
  • Share this page with Twitter (Opens in a new window)
  • Share this page with Google+ (Opens in a new window)
  • Share this page with Delicious (Opens in a new window)