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» Integrating Microarray Data by Consensus Clustering
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JBI
2004
171views Bioinformatics» more  JBI 2004»
13 years 7 months ago
Consensus Clustering and Functional Interpretation of Gene Expression Data
Microarray analysis using clustering algorithms can suffer from lack of inter-method consistency in assigning related gene-expression profiles to clusters. Obtaining a consensus s...
Paul Kellam, Stephen Swift, Allan Tucker, Veronica...
ICDM
2007
IEEE
149views Data Mining» more  ICDM 2007»
13 years 12 months ago
Solving Consensus and Semi-supervised Clustering Problems Using Nonnegative Matrix Factorization
Consensus clustering and semi-supervised clustering are important extensions of the standard clustering paradigm. Consensus clustering (also known as aggregation of clustering) ca...
Tao Li, Chris H. Q. Ding, Michael I. Jordan
BMCBI
2008
104views more  BMCBI 2008»
13 years 5 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...
BMCBI
2008
204views more  BMCBI 2008»
13 years 5 months ago
EST2uni: an open, parallel tool for automated EST analysis and database creation, with a data mining web interface and microarra
Background: Expressed sequence tag (EST) collections are composed of a high number of single-pass, redundant, partial sequences, which need to be processed, clustered, and annotat...
Javier Forment, Francisco Gilabert Villamón...