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RECOMB
2002
Springer
14 years 7 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
2004
169views more  BMCBI 2004»
13 years 6 months ago
A power law global error model for the identification of differentially expressed genes in microarray data
Background: High-density oligonucleotide microarray technology enables the discovery of genes that are transcriptionally modulated in different biological samples due to physiolog...
Norman Pavelka, Mattia Pelizzola, Caterina Vizzard...
ISMB
2004
13 years 8 months ago
Predicting gene regulation by sigma factors in Bacillus subtilis from genome-wide data
Motivation: Sigma factors regulate the expression of genes in Bacillus subtilis at the transcriptional level. First we assess the ability of currently available gene regulatory ne...
Michiel J. L. de Hoon, Yuko Makita, Seiya Imoto, K...
BMCBI
2010
136views more  BMCBI 2010»
13 years 6 months ago
Bias correction and Bayesian analysis of aggregate counts in SAGE libraries
Background: Tag-based techniques, such as SAGE, are commonly used to sample the mRNA pool of an organism's transcriptome. Incomplete digestion during the tag formation proces...
Russell L. Zaretzki, Michael A. Gilchrist, William...
BMCBI
2006
156views more  BMCBI 2006»
13 years 6 months ago
Bayesian models for pooling microarray studies with multiple sources of replications
Background: Biologists often conduct multiple but different cDNA microarray studies that all target the same biological system or pathway. Within each study, replicate slides with...
Erin M. Conlon, Joon J. Song, Jun S. Liu