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» Microarray Gene Expression Data Analysis
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IJDMB
2008
132views more  IJDMB 2008»
14 years 9 months ago
A Bayesian framework for knowledge driven regression model in micro-array data analysis
: This paper addresses the sparse data problem in the linear regression model, namely the number of variables is significantly larger than the number of the data points for regress...
Rong Jin, Luo Si, Christina Chan
BMCBI
2007
134views more  BMCBI 2007»
14 years 9 months ago
Nearest Neighbor Networks: clustering expression data based on gene neighborhoods
Background: The availability of microarrays measuring thousands of genes simultaneously across hundreds of biological conditions represents an opportunity to understand both indiv...
Curtis Huttenhower, Avi I. Flamholz, Jessica N. La...
BMCBI
2008
135views more  BMCBI 2008»
14 years 9 months ago
Using Generalized Procrustes Analysis (GPA) for normalization of cDNA microarray data
Background: Normalization is essential in dual-labelled microarray data analysis to remove nonbiological variations and systematic biases. Many normalization methods have been use...
Huiling Xiong, Dapeng Zhang, Christopher J. Martyn...
IV
2007
IEEE
178views Visualization» more  IV 2007»
15 years 4 months ago
Viewing the Larger Context of Genomic Data through Horizontal Integration
Genomics is an important emerging scientific field that relies on meaningful data visualization as a key step in analysis. Specifically, most investigation of gene expression micr...
Matthew A. Hibbs, Grant Wallace, Maitreya J. Dunha...
GCB
2010
Springer
204views Biometrics» more  GCB 2010»
14 years 7 months ago
Learning Pathway-based Decision Rules to Classify Microarray Cancer Samples
: Despite recent advances in DNA chip technology current microarray gene expression studies are still affected by high noise levels, small sample sizes and large numbers of uninfor...
Enrico Glaab, Jonathan M. Garibaldi, Natalio Krasn...