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» Clustering cancer gene expression data: a comparative study
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BMCBI
2005
113views more  BMCBI 2005»
15 years 6 months ago
Normal uniform mixture differential gene expression detection for cDNA microarrays
Background: One of the primary tasks in analysing gene expression data is finding genes that are differentially expressed in different samples. Multiple testing issues due to the ...
Nema Dean, Adrian E. Raftery
BMCBI
2010
135views more  BMCBI 2010»
15 years 6 months ago
Simple and flexible classification of gene expression microarrays via Swirls and Ripples
Background: A simple classification rule with few genes and parameters is desirable when applying a classification rule to new data. One popular simple classification rule, diagon...
Stuart G. Baker
BMCBI
2007
146views more  BMCBI 2007»
15 years 6 months ago
Bayesian hierarchical model for transcriptional module discovery by jointly modeling gene expression and ChIP-chip data
Background: Transcriptional modules (TM) consist of groups of co-regulated genes and transcription factors (TF) regulating their expression. Two high-throughput (HT) experimental ...
Xiangdong Liu, Walter J. Jessen, Siva Sivaganesan,...
RECOMB
2002
Springer
16 years 6 months ago
A new approach to analyzing gene expression time series data
We present algorithms for time-series gene expression analysis that permit the principled estimation of unobserved timepoints, clustering, and dataset alignment. Each expression p...
Ziv Bar-Joseph, Georg Gerber, David K. Gifford, To...
BMCBI
2007
129views more  BMCBI 2007»
15 years 6 months ago
HoughFeature, a novel method for assessing drug effects in three-color cDNA microarray experiments
Background: Three-color microarray experiments can be performed to assess drug effects on the genomic scale. The methodology may be useful in shortening the cycle, reducing the co...
Hongya Zhao, Hong Yan