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» Simultaneously Segmenting Multiple Gene Expression Time Cour...
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2005
Springer
13 years 10 months ago
Order Preserving Clustering over Multiple Time Course Experiments
Abstract. Clustering still represents the most commonly used technique to analyze gene expression data—be it classical clustering approaches that aim at finding biologically rel...
Stefan Bleuler, Eckart Zitzler
BMCBI
2008
154views more  BMCBI 2008»
13 years 4 months ago
Bayesian models and meta analysis for multiple tissue gene expression data following corticosteroid administration
Background: This paper addresses key biological problems and statistical issues in the analysis of large gene expression data sets that describe systemic temporal response cascade...
Yulan Liang, Arpad Kelemen
BMCBI
2006
155views more  BMCBI 2006»
13 years 4 months ago
AffyMiner: mining differentially expressed genes and biological knowledge in GeneChip microarray data
Background: DNA microarrays are a powerful tool for monitoring the expression of tens of thousands of genes simultaneously. With the advance of microarray technology, the challeng...
Guoqing Lu, The V. Nguyen, Yuannan Xia, Michael Fr...
BMCBI
2011
12 years 11 months ago
A Platform for Processing Expression of Short Time Series (PESTS)
Background: Time course microarray profiles examine the expression of genes over a time domain. They are necessary in order to determine the complete set of genes that are dynamic...
Anshu Sinha, Marianthi Markatou