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» Combining microarrays and genetic analysis
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CSB
2002
IEEE
169views Bioinformatics» more  CSB 2002»
14 years 2 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...
FUIN
2011
358views Cryptology» more  FUIN 2011»
13 years 1 months ago
Unsupervised and Supervised Learning Approaches Together for Microarray Analysis
In this article, a novel concept is introduced by using both unsupervised and supervised learning. For unsupervised learning, the problem of fuzzy clustering in microarray data as ...
Indrajit Saha, Ujjwal Maulik, Sanghamitra Bandyopa...
BMCBI
2008
115views more  BMCBI 2008»
13 years 10 months ago
Genome-scale cluster analysis of replicated microarrays using shrinkage correlation coefficient
Background: Currently, clustering with some form of correlation coefficient as the gene similarity metric has become a popular method for profiling genomic data. The Pearson corre...
Jianchao Yao, Chunqi Chang, Mari L. Salmi, Yeung S...
BMCBI
2008
129views more  BMCBI 2008»
13 years 10 months ago
EMAAS: An extensible grid-based Rich Internet Application for microarray data analysis and management
Background: Microarray experimentation requires the application of complex analysis methods as well as the use of non-trivial computer technologies to manage the resultant large d...
Geraint Barton, J. C. Abbott, Norie Chiba, D. W. H...
BMCBI
2006
130views more  BMCBI 2006»
13 years 10 months ago
CARMA: A platform for analyzing microarray datasets that incorporate replicate measures
Background: The incorporation of statistical models that account for experimental variability provides a necessary framework for the interpretation of microarray data. A robust ex...
Kevin A. Greer, Matthew R. McReynolds, Heddwen L. ...