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BMCBI
2010
181views more  BMCBI 2010»
13 years 5 months ago
Intensity dependent estimation of noise in microarrays improves detection of differentially expressed genes
Background: In many microarray experiments, analysis is severely hindered by a major difficulty: the small number of samples for which expression data has been measured. When one ...
Amit Zeisel, Amnon Amir, Wolfgang J. Köstler,...
BMCBI
2006
88views more  BMCBI 2006»
13 years 5 months ago
Effect of various normalization methods on Applied Biosystems expression array system data
Background: DNA microarray technology provides a powerful tool for characterizing gene expression on a genome scale. While the technology has been widely used in discovery-based m...
Catalin C. Barbacioru, Yulei Wang, Roger D. Canale...
BIBE
2004
IEEE
107views Bioinformatics» more  BIBE 2004»
13 years 9 months ago
Enhanced pClustering and Its Applications to Gene Expression Data
Clustering has been one of the most popular methods to discover useful biological insights from DNA microarray. An interesting paradigm is simultaneous clustering of both genes an...
Sungroh Yoon, Christine Nardini, Luca Benini, Giov...
BMCBI
2004
169views more  BMCBI 2004»
13 years 5 months ago
A power law global error model for the identification of differentially expressed genes in microarray data
Background: High-density oligonucleotide microarray technology enables the discovery of genes that are transcriptionally modulated in different biological samples due to physiolog...
Norman Pavelka, Mattia Pelizzola, Caterina Vizzard...
BMCBI
2007
163views more  BMCBI 2007»
13 years 5 months ago
Use of genomic DNA control features and predicted operon structure in microarray data analysis: ArrayLeaRNA - a Bayesian approac
Background: Microarrays are widely used for the study of gene expression; however deciding on whether observed differences in expression are significant remains a challenge. Resul...
Carmen Pin, Mark Reuter