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CLEIEJ
2007
152views more  CLEIEJ 2007»
13 years 7 months ago
Gene Expression Analysis using Markov Chains extracted from RNNs
Abstract. This paper present a new approach for the analysis of gene expression, by extracting a Markov Chain from trained Recurrent Neural Networks (RNNs). A lot of microarray dat...
Igor Lorenzato Almeida, Denise Regina Pechmann Sim...
CSB
2005
IEEE
205views Bioinformatics» more  CSB 2005»
14 years 1 months ago
Fractal Clustering for Microarray Data Analysis
DNA microarray experiments generate a substantial amount of information about global gene expression. Gene expression profiles can be represented as points in multi-dimensional sp...
Lu-Yong Wang, Ammaiappan Balasubramanian, Amit Cha...
BMCBI
2004
146views more  BMCBI 2004»
13 years 7 months ago
Defining transcriptional networks through integrative modeling of mRNA expression and transcription factor binding data
Background: Functional genomics studies are yielding information about regulatory processes in the cell at an unprecedented scale. In the yeast S. cerevisiae, DNA microarrays have...
Feng Gao, Barrett C. Foat, Harmen J. Bussemaker
BMCBI
2004
115views more  BMCBI 2004»
13 years 7 months ago
Quantifying the relationship between co-expression, co-regulation and gene function
Background: It is thought that genes with similar patterns of mRNA expression and genes with similar functions are likely to be regulated via the same mechanisms. It has been diff...
Dominic J. Allocco, Isaac S. Kohane, Atul J. Butte
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...