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» Smoothing Gene Expression Using Biological Networks
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JCB
2002
160views more  JCB 2002»
13 years 8 months ago
Inference from Clustering with Application to Gene-Expression Microarrays
There are many algorithms to cluster sample data points based on nearness or a similarity measure. Often the implication is that points in different clusters come from different u...
Edward R. Dougherty, Junior Barrera, Marcel Brun, ...
BMCBI
2007
174views more  BMCBI 2007»
13 years 9 months ago
Inferring activity changes of transcription factors by binding association with sorted expression profiles
Background: The identification of transcription factors (TFs) associated with a biological process is fundamental to understanding its regulatory mechanisms. From microarray data,...
Chao Cheng, Xiting Yan, Fengzhu Sun, Lei M. Li
BMCBI
2006
216views more  BMCBI 2006»
13 years 9 months ago
Machine learning approaches to supporting the identification of photoreceptor-enriched genes based on expression data
Background: Retinal photoreceptors are highly specialised cells, which detect light and are central to mammalian vision. Many retinal diseases occur as a result of inherited dysfu...
Haiying Wang, Huiru Zheng, David Simpson, Francisc...
RECOMB
2002
Springer
14 years 9 months ago
Phase-independent rhythmic analysis of genome-wide expression patterns
We introduce a model-based analysis technique for extracting and characterizing rhythmic expression pro les from genome-wide DNA microarray hybridization data. These patterns are ...
Christopher James Langmead, Anthony K. Yan, C. Rob...
CSB
2005
IEEE
146views Bioinformatics» more  CSB 2005»
14 years 2 months ago
Multi-Metric and Multi-Substructure Biclustering Analysis for Gene Expression Data
A good number of biclustering algorithms have been proposed for grouping gene expression data. Many of them have adopted matrix norms to define the similarity score of a bicluste...
Sun-Yuan Kung, Man-Wai Mak, Ilias Tagkopoulos