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» A factor model to analyze heterogeneity in gene expression
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BMCBI
2005
113views more  BMCBI 2005»
14 years 9 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
80
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BIOINFORMATICS
2006
124views more  BIOINFORMATICS 2006»
14 years 9 months ago
Probabilistic inference of transcription factor concentrations and gene-specific regulatory activities
Motivation Quantitative estimation of the regulatory relationship between transcription factors and genes is a fundamental stepping stone when trying to develop models of cellular...
Guido Sanguinetti, Neil D. Lawrence, Magnus Rattra...
89
Voted
BMCBI
2006
120views more  BMCBI 2006»
14 years 9 months ago
An improved distance measure between the expression profiles linking co-expression and co-regulation in mouse
Background: Many statistical algorithms combine microarray expression data and genome sequence data to identify transcription factor binding motifs in the low eukaryotic genomes. ...
Ryung S. Kim, Hongkai Ji, Wing Hung Wong
BMCBI
2006
151views more  BMCBI 2006»
14 years 9 months ago
Modeling Sage data with a truncated gamma-Poisson model
Background: Serial Analysis of Gene Expressions (SAGE) produces gene expression measurements on a discrete scale, due to the finite number of molecules in the sample. This means t...
Helene H. Thygesen, Aeilko H. Zwinderman
BMCBI
2007
154views more  BMCBI 2007»
14 years 9 months ago
Classification of heterogeneous microarray data by maximum entropy kernel
Background: There is a large amount of microarray data accumulating in public databases, providing various data waiting to be analyzed jointly. Powerful kernel-based methods are c...
Wataru Fujibuchi, Tsuyoshi Kato