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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...
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...
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BMCBI
2007
147views more  BMCBI 2007»
14 years 9 months ago
Statistical analysis and significance testing of serial analysis of gene expression data using a Poisson mixture model
Background: Serial analysis of gene expression (SAGE) is used to obtain quantitative snapshots of the transcriptome. These profiles are count-based and are assumed to follow a Bin...
Scott D. Zuyderduyn
WILF
2007
Springer
147views Fuzzy Logic» more  WILF 2007»
15 years 3 months ago
Fuzzy Ensemble Clustering for DNA Microarray Data Analysis
Two major problems related the unsupervised analysis of gene expression data are represented by the accuracy and reliability of the discovered clusters, and by the biological fact ...
Roberto Avogadri, Giorgio Valentini
KDD
2006
ACM
156views Data Mining» more  KDD 2006»
15 years 10 months ago
Discovering significant OPSM subspace clusters in massive gene expression data
Order-preserving submatrixes (OPSMs) have been accepted as a biologically meaningful subspace cluster model, capturing the general tendency of gene expressions across a subset of ...
Byron J. Gao, Obi L. Griffith, Martin Ester, Steve...