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» Systematic Evaluation of Scaling Methods for Gene Expression...
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BMCBI
2008
115views more  BMCBI 2008»
13 years 7 months ago
Principal components analysis based methodology to identify differentially expressed genes in time-course microarray data
Background: Time-course microarray experiments are being increasingly used to characterize dynamic biological processes. In these experiments, the goal is to identify genes differ...
Sudhakar Jonnalagadda, Rajagopalan Srinivasan
TCBB
2010
136views more  TCBB 2010»
13 years 5 months ago
Integrating Data Clustering and Visualization for the Analysis of 3D Gene Expression Data
— The recent development of methods for extracting precise measurements of spatial gene expression patterns from three-dimensional (3D) image data opens the way for new analyses ...
Oliver Rübel, Gunther H. Weber, Min-Yu Huang,...
ISMB
2000
13 years 8 months ago
Genes, Themes, and Microarrays: Using Information Retrieval for Large-Scale Gene Analysis
The immensevolumeof data resulting from DNAmicroarray experiments, accompaniedby an increase in the numberof publications discussing gene-related discoveries, presents a majordata...
Hagit Shatkay, Stephen Edwards, W. John Wilbur, Ma...
BMCBI
2006
131views more  BMCBI 2006»
13 years 7 months ago
The statistics of identifying differentially expressed genes in Expresso and TM4: a comparison
Background: Analysis of DNA microarray data takes as input spot intensity measurements from scanner software and returns differential expression of genes between two conditions, t...
Allan A. Sioson, Shrinivasrao P. Mane, Pinghua Li,...
BMCBI
2008
104views more  BMCBI 2008»
13 years 7 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...