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BMCBI
2004
158views more  BMCBI 2004»
13 years 6 months ago
A novel Mixture Model Method for identification of differentially expressed genes from DNA microarray data
Background: The main goal in analyzing microarray data is to determine the genes that are differentially expressed across two types of tissue samples or samples obtained under two...
Kayvan Najarian, Maryam Zaheri, Ali Ajdari Rad, Si...
BMCBI
2007
163views more  BMCBI 2007»
13 years 6 months ago
Use of genomic DNA control features and predicted operon structure in microarray data analysis: ArrayLeaRNA - a Bayesian approac
Background: Microarrays are widely used for the study of gene expression; however deciding on whether observed differences in expression are significant remains a challenge. Resul...
Carmen Pin, Mark Reuter
BMCBI
2007
143views more  BMCBI 2007»
13 years 6 months ago
Factor analysis for gene regulatory networks and transcription factor activity profiles
Background: Most existing algorithms for the inference of the structure of gene regulatory networks from gene expression data assume that the activity levels of transcription fact...
Iosifina Pournara, Lorenz Wernisch
BMCBI
2005
145views more  BMCBI 2005»
13 years 6 months ago
CAGER: classification analysis of gene expression regulation using multiple information sources
Background: Many classification approaches have been applied to analyzing transcriptional regulation of gene expressions. These methods build models that can explain a gene's...
Jianhua Ruan, Weixiong Zhang
BMCBI
2010
124views more  BMCBI 2010»
13 years 6 months ago
A factor model to analyze heterogeneity in gene expression
Background: Microarray technology allows the simultaneous analysis of thousands of genes within a single experiment. Significance analyses of transcriptomic data ignore the gene d...
Yuna Blum, Guillaume Le Mignon, Sandrine Lagarrigu...