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» Gene set analysis for longitudinal gene expression data
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IJPP
2008
158views more  IJPP 2008»
13 years 7 months ago
The ParTriCluster Algorithm for Gene Expression Analysis
Analyzing gene expression patterns is becoming a highly relevant task in the Bioinformatics area. This analysis makes it possible to determine the behavior patterns of genes under...
Renata Braga Araújo, Guilherme Henrique Tri...
BMCBI
2006
129views more  BMCBI 2006»
13 years 7 months ago
Identifying genes that contribute most to good classification in microarrays
Background: The goal of most microarray studies is either the identification of genes that are most differentially expressed or the creation of a good classification rule. The dis...
Stuart G. Baker, Barnett S. Kramer
CSB
2002
IEEE
169views Bioinformatics» more  CSB 2002»
14 years 19 days ago
Bayesian Network and Nonparametric Heteroscedastic Regression for Nonlinear Modeling of Genetic Network
We propose a new statistical method for constructing a genetic network from microarray gene expression data by using a Bayesian network. An essential point of Bayesian network con...
Seiya Imoto, SunYong Kim, Takao Goto, Sachiyo Abur...
RECOMB
2001
Springer
14 years 8 months ago
Context-specific Bayesian clustering for gene expression data
The recent growth in genomic data and measurements of genome-wide expression patterns allows us to apply computational tools to examine gene regulation by transcription factors. I...
Yoseph Barash, Nir Friedman
SDM
2008
SIAM
157views Data Mining» more  SDM 2008»
13 years 9 months ago
ROC-tree: A Novel Decision Tree Induction Algorithm Based on Receiver Operating Characteristics to Classify Gene Expression Data
Gene expression information from microarray experiments is a primary form of data for biological analysis and can offer insights into disease processes and cellular behaviour. Suc...
M. Maruf Hossain, Md. Rafiul Hassan, James Bailey