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» Combined Gene Selection Methods for Microarray Data Analysis
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BMCBI
2010
142views more  BMCBI 2010»
15 years 15 days ago
Comparison of Beta-value and M-value methods for quantifying methylation levels by microarray analysis
Background: High-throughput profiling of DNA methylation status of CpG islands is crucial to understand the epigenetic regulation of genes. The microarray-based Infinium methylati...
Pan Du, Xiao Zhang, Chiang-Ching Huang, Nadereh Ja...
BMCBI
2004
90views more  BMCBI 2004»
15 years 2 months ago
Statistical monitoring of weak spots for improvement of normalization and ratio estimates in microarrays
Background: Several aspects of microarray data analysis are dependent on identification of genes expressed at or near the limits of detection. For example, regression-based normal...
Igor Dozmorov, Nicholas Knowlton, Yuhong Tang, Mic...
BMCBI
2008
122views more  BMCBI 2008»
15 years 3 months ago
Determining gene expression on a single pair of microarrays
Background: In microarray experiments the numbers of replicates are often limited due to factors such as cost, availability of sample or poor hybridization. There are currently fe...
Robert W. Reid, Anthony A. Fodor
PKDD
2009
Springer
148views Data Mining» more  PKDD 2009»
15 years 9 months ago
Feature Selection by Transfer Learning with Linear Regularized Models
Abstract. This paper presents a novel feature selection method for classification of high dimensional data, such as those produced by microarrays. It includes a partial supervisio...
Thibault Helleputte, Pierre Dupont
BMCBI
2010
115views more  BMCBI 2010»
15 years 3 months ago
Importance of replication in analyzing time-series gene expression data: Corticosteroid dynamics and circadian patterns in rat l
Background: Microarray technology is a powerful and widely accepted experimental technique in molecular biology that allows studying genome wide transcriptional responses. However...
Tung T. Nguyen, Richard R. Almon, Debra C. DuBois,...