2011 2nd National Conference on Emerging Trends and Applications in Computer Science 2011
DOI: 10.1109/ncetacs.2011.5751377
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Gene expression data clustering analysis: A survey

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Cited by 10 publications
(5 citation statements)
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“…Another way to cluster genes is to group co-expressed genes in the same cluster, which do not necessarily have similar functions [38]. For a survey on clustering genes, the reader is referred to [39, 40] and references therein. Our method is decoupled from the clustering step.…”
Section: Resultsmentioning
confidence: 99%
“…Another way to cluster genes is to group co-expressed genes in the same cluster, which do not necessarily have similar functions [38]. For a survey on clustering genes, the reader is referred to [39, 40] and references therein. Our method is decoupled from the clustering step.…”
Section: Resultsmentioning
confidence: 99%
“…Recent developments in the area of DNA microarray technology, such as classification, clustering, biclustering, triclustering (Jiang et al 2004;Ahmed et al 2011;Mahanta et al 2011;Nagi et al 2011a) and feature selection techniques (Schadt et al 2001;Van Hulse et al 2012) have made it possible for scientists to monitor the expression level of thousands of genes with a single experiment (Schena et al 1995;Lockhart et al 1996). This helps in (i) classifying diseases according to varying expression levels in normal and tumor cells, (ii) uncovering gene-gene relationship, and (iii) identifying genes responsible for the development of diseases.…”
Section: Introductionmentioning
confidence: 99%
“…This requires that the existing algorithms be enhanced to speedily detect clusters of high quality. In sharp contrast to subspace clustering algorithms, traditional clustering algorithms consider all of the dimensions of the dataset in discovering clusters although many of the dimensions are often irrelevant [2][3] [4]. These irrelevant dimensions can confuse clustering algorithms by hiding clusters in noisy data.…”
Section: Introductionmentioning
confidence: 99%