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CSB
2002
IEEE
169views Bioinformatics» more  CSB 2002»
13 years 9 months 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...
BMCBI
2008
96views more  BMCBI 2008»
13 years 4 months ago
Use of normalization methods for analysis of microarrays containing a high degree of gene effects
Background: High-throughput microarrays are widely used to study gene expression across tissues and developmental stages. Analysis of gene expression data is challenging in these ...
Terri T. Ni, William J. Lemon, Yu Shyr, Tao P. Zho...
BMCBI
2004
158views more  BMCBI 2004»
13 years 4 months ago
A novel Mixture Model Method for identification of differentially expressed genes from DNA microarray data
Background: The main goal in analyzing microarray data is to determine the genes that are differentially expressed across two types of tissue samples or samples obtained under two...
Kayvan Najarian, Maryam Zaheri, Ali Ajdari Rad, Si...
BMCBI
2010
118views more  BMCBI 2010»
13 years 4 months ago
Testing for mean and correlation changes in microarray experiments: an application for pathway analysis
Background: Microarray experiments examine the change in transcript levels of tens of thousands of genes simultaneously. To derive meaningful data, biologists investigate the resp...
Mayer Alvo, Zhongzhu Liu, Andrew Williams, Carole ...
BIOINFORMATICS
2005
151views more  BIOINFORMATICS 2005»
13 years 4 months ago
Differential and trajectory methods for time course gene expression data
Motivation: The issue of high dimensionality in microarray data has been, and remains, a hot topic in statistical and computational analysis. Efficient gene filtering and differen...
Yulan Liang, Bamidele Tayo, Xueya Cai, Arpad Kelem...