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» A factor model to analyze heterogeneity in gene expression
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BMCBI
2008
159views more  BMCBI 2008»
14 years 9 months ago
Multivariate hierarchical Bayesian model for differential gene expression analysis in microarray experiments
Background: Identification of differentially expressed genes is a typical objective when analyzing gene expression data. Recently, Bayesian hierarchical models have become increas...
Hongya Zhao, Kwok-Leung Chan, Lee-Ming Cheng, Hong...
BMCBI
2010
165views more  BMCBI 2010»
14 years 9 months ago
Bayesian integrated modeling of expression data: a case study on RhoG
Background: DNA microarrays provide an efficient method for measuring activity of genes in parallel and even covering all the known transcripts of an organism on a single array. T...
Rashi Gupta, Dario Greco, Petri Auvinen, Elja Arja...
BMCBI
2006
123views more  BMCBI 2006»
14 years 9 months ago
Characterizing disease states from topological properties of transcriptional regulatory networks
Background: High throughput gene expression experiments yield large amounts of data that can augment our understanding of disease processes, in addition to classifying samples. He...
David Tuck, Harriet Kluger, Yuval Kluger
BMCBI
2008
122views more  BMCBI 2008»
14 years 9 months ago
Determining gene expression on a single pair of microarrays
Background: In microarray experiments the numbers of replicates are often limited due to factors such as cost, availability of sample or poor hybridization. There are currently fe...
Robert W. Reid, Anthony A. Fodor
BMCBI
2011
14 years 1 months ago
RegNetB: Predicting Relevant Regulator-Gene Relationships in Localized Prostate Tumor Samples
Background: A central question in cancer biology is what changes cause a healthy cell to form a tumor. Gene expression data could provide insight into this question, but it is dif...
Angel Alvarez, Peter J. Woolf