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» Analysis of variance components in gene expression data
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BMCBI
2006
106views more  BMCBI 2006»
14 years 9 months ago
Methodological study of affine transformations of gene expression data with proposed robust non-parametric multi-dimensional nor
Background: Low-level processing and normalization of microarray data are most important steps in microarray analysis, which have profound impact on downstream analysis. Multiple ...
Henrik Bengtsson, Ola Hössjer
BMCBI
2007
134views more  BMCBI 2007»
14 years 10 months ago
Nearest Neighbor Networks: clustering expression data based on gene neighborhoods
Background: The availability of microarrays measuring thousands of genes simultaneously across hundreds of biological conditions represents an opportunity to understand both indiv...
Curtis Huttenhower, Avi I. Flamholz, Jessica N. La...
BMCBI
2005
153views more  BMCBI 2005»
14 years 9 months ago
A comparative review of estimates of the proportion unchanged genes and the false discovery rate
Background: In the analysis of microarray data one generally produces a vector of p-values that for each gene give the likelihood of obtaining equally strong evidence of change by...
Per Broberg
BMCBI
2008
104views more  BMCBI 2008»
14 years 10 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...
ISMB
2000
14 years 11 months ago
Mining for Putative Regulatory Elements in the Yeast Genome Using Gene Expression Data
We have developed a set of methods and tools for automatic discovery of putative regulatory signals in genome sequences. The analysis pipeline consists of gene expression data clu...
Jaak Vilo, Alvis Brazma, Inge Jonassen, Alan J. Ro...