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» Rich probabilistic models for gene expression
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NIPS
2004
13 years 9 months ago
Probabilistic Inference of Alternative Splicing Events in Microarray Data
Alternative splicing (AS) is an important and frequent step in mammalian gene expression that allows a single gene to specify multiple products, and is crucial for the regulation ...
Ofer Shai, Brendan J. Frey, Quaid Morris, Qun Pan,...
RECOMB
2002
Springer
14 years 8 months ago
Discovering local structure in gene expression data: the order-preserving submatrix problem
This paper concerns the discovery of patterns in gene expression matrices, in which each element gives the expression level of a given gene in a given experiment. Most existing me...
Amir Ben-Dor, Benny Chor, Richard M. Karp, Zohar Y...
BIOINFORMATICS
2006
118views more  BIOINFORMATICS 2006»
13 years 7 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
2006
239views more  BMCBI 2006»
13 years 7 months ago
Applying dynamic Bayesian networks to perturbed gene expression data
Background: A central goal of molecular biology is to understand the regulatory mechanisms of gene transcription and protein synthesis. Because of their solid basis in statistics,...
Norbert Dojer, Anna Gambin, Andrzej Mizera, Bartek...
BMCBI
2005
140views more  BMCBI 2005»
13 years 7 months ago
Dissecting systems-wide data using mixture models: application to identify affected cellular processes
Background: Functional analysis of data from genome-scale experiments, such as microarrays, requires an extensive selection of differentially expressed genes. Under many condition...
J. Peter Svensson, Renée X. de Menezes, Ing...