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BIOINFORMATICS
2006
118views more  BIOINFORMATICS 2006»
13 years 8 months ago
A probabilistic dynamical model for quantitative inference of the regulatory mechanism of transcription
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, Magnus Rattray, Neil D. Lawrenc...
BMCBI
2004
106views more  BMCBI 2004»
13 years 8 months ago
Spotting effect in microarray experiments
Background: Microarray data must be normalized because they suffer from multiple biases. We have identified a source of spatial experimental variability that significantly affects...
Tristan Mary-Huard, Jean-Jacques Daudin, Sté...
BMCBI
2007
185views more  BMCBI 2007»
13 years 8 months ago
GEDI: a user-friendly toolbox for analysis of large-scale gene expression data
Background: Several mathematical and statistical methods have been proposed in the last few years to analyze microarray data. Most of those methods involve complicated formulas, a...
André Fujita, João Ricardo Sato, Car...
JBI
2002
13 years 8 months ago
Revising regulatory networks: from expression data to linear causal models
Discovering the complex regulatory networks that govern mRNA expression is an important but difficult problem. Many current approaches use only expression data from microarrays to...
Stephen D. Bay, Jeff Shrager, Andrew Pohorille, Pa...
BMCBI
2008
202views more  BMCBI 2008»
13 years 8 months ago
Network motif-based identification of transcription factor-target gene relationships by integrating multi-source biological data
Background: Integrating data from multiple global assays and curated databases is essential to understand the spatiotemporal interactions within cells. Different experiments measu...
Yuji Zhang, Jianhua Xuan, Benildo de los Reyes, Ro...