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» A factor model to analyze heterogeneity in gene expression
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BMCBI
2008
126views more  BMCBI 2008»
14 years 9 months ago
Relating gene expression data on two-component systems to functional annotations in Escherichia coli
Background: Obtaining physiological insights from microarray experiments requires computational techniques that relate gene expression data to functional information. Traditionall...
Anne M. Denton, Jianfei Wu, Megan K. Townsend, Pre...
BMCBI
2010
85views more  BMCBI 2010»
14 years 9 months ago
Robust test method for time-course microarray experiments
Background: In a time-course microarray experiment, the expression level for each gene is observed across a number of time-points in order to characterize the temporal trajectorie...
Insuk Sohn, Kouros Owzar, Stephen L. George, Sujon...
BMCBI
2004
98views more  BMCBI 2004»
14 years 9 months ago
Incidence of "quasi-ditags" in catalogs generated by Serial Analysis of Gene Expression (SAGE)
Background: Serial Analysis of Gene Expression (SAGE) is a functional genomic technique that quantitatively analyzes the cellular transcriptome. The analysis of SAGE libraries rel...
Sergey V. Anisimov, Alexei A. Sharov
RECOMB
2002
Springer
15 years 10 months ago
From promoter sequence to expression: a probabilistic framework
We present a probabilistic framework that models the process by which transcriptional binding explains the mRNA expression of different genes. Our joint probabilistic model unifie...
Eran Segal, Yoseph Barash, Itamar Simon, Nir Fried...
BMCBI
2008
166views more  BMCBI 2008»
14 years 9 months ago
Learning transcriptional regulatory networks from high throughput gene expression data using continuous three-way mutual informa
Background: Probability based statistical learning methods such as mutual information and Bayesian networks have emerged as a major category of tools for reverse engineering mecha...
Weijun Luo, Kurt D. Hankenson, Peter J. Woolf