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» Network constrained clustering for gene microarray data
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BMCBI
2008
121views more  BMCBI 2008»
14 years 9 months ago
Microarray data mining using landmark gene-guided clustering
Background: Clustering is a popular data exploration technique widely used in microarray data analysis. Most conventional clustering algorithms, however, generate only one set of ...
Pankaj Chopra, Jaewoo Kang, Jiong Yang, HyungJun C...
BMCBI
2008
104views more  BMCBI 2008»
14 years 9 months ago
Missing value imputation improves clustering and interpretation of gene expression microarray data
Background: Missing values frequently pose problems in gene expression microarray experiments as they can hinder downstream analysis of the datasets. While several missing value i...
Johannes Tuikkala, Laura Elo, Olli Nevalainen, Ter...
JCB
2002
160views more  JCB 2002»
14 years 9 months ago
Inference from Clustering with Application to Gene-Expression Microarrays
There are many algorithms to cluster sample data points based on nearness or a similarity measure. Often the implication is that points in different clusters come from different u...
Edward R. Dougherty, Junior Barrera, Marcel Brun, ...
BIOINFORMATICS
2007
190views more  BIOINFORMATICS 2007»
14 years 9 months ago
Towards clustering of incomplete microarray data without the use of imputation
Motivation: Clustering technique is used to find groups of genes that show similar expression patterns under multiple experimental conditions. Nonetheless, the results obtained by...
Dae-Won Kim, Ki Young Lee, Kwang H. Lee, Doheon Le...
ICDM
2006
IEEE
129views Data Mining» more  ICDM 2006»
15 years 3 months ago
Consensus Clustering for Detection of Overlapping Clusters in Microarray Data
Most clustering algorithms are partitional in nature, assigning each data point to exactly one cluster. However, several real world datasets have inherently overlapping clusters i...
Meghana Deodhar, Joydeep Ghosh