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» Integrative missing value estimation for microarray data
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BIOINFORMATICS
2007
190views more  BIOINFORMATICS 2007»
13 years 5 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...
BMCBI
2007
62views more  BMCBI 2007»
13 years 5 months ago
Missing channels in two-colour microarray experiments: Combining single-channel and two-channel data
Background: There are mechanisms, notably ozone degradation, that can damage a single channel of two-channel microarray experiments. Resulting analyses therefore often choose betw...
Andy G. Lynch, David E. Neal, John D. Kelly, Glyn ...
BMCBI
2006
103views more  BMCBI 2006»
13 years 5 months ago
Improving missing value imputation of microarray data by using spot quality weights
Background: Microarray technology has become popular for gene expression profiling, and many analysis tools have been developed for data interpretation. Most of these tools requir...
Peter Johansson, Jari Häkkinen
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
2007
194views more  BMCBI 2007»
13 years 5 months ago
A meta-data based method for DNA microarray imputation
Background: DNA microarray experiments are conducted in logical sets, such as time course profiling after a treatment is applied to the samples, or comparisons of the samples unde...
Rebecka Jörnsten, Ming Ouyang, Hui-Yu Wang