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BMCBI
2006
116views more  BMCBI 2006»
13 years 7 months ago
Integrative missing value estimation for microarray data
Background: Missing value estimation is an important preprocessing step in microarray analysis. Although several methods have been developed to solve this problem, their performan...
Jianjun Hu, Haifeng Li, Michael S. Waterman, Xiang...
BMCBI
2007
194views more  BMCBI 2007»
13 years 7 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
BIBE
2007
IEEE
153views Bioinformatics» more  BIBE 2007»
13 years 9 months ago
Combined expression data with missing values and gene interaction network analysis: a Markovian integrated approach
—DNA microarray technologies provide means for monitoring in the order of tens of thousands of gene expression levels quantitatively and simultaneously. However data generated in...
Juliette Blanchet, Matthieu Vignes
BIOINFORMATICS
2007
190views more  BIOINFORMATICS 2007»
13 years 7 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...
WCE
2007
13 years 8 months ago
A Fast Multivariate Nearest Neighbour Imputation Algorithm
— Imputation of missing data is important in many areas, such as reducing non-response bias in surveys and maintaining medical documentation. Nearest neighbour (NN) imputation al...
Norman Solomon, Giles Oatley, Kenneth McGarry