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BMCBI
2002
195views more  BMCBI 2002»
14 years 9 months ago
Clustering of the SOM easily reveals distinct gene expression patterns: results of a reanalysis of lymphoma study
Background: A method to evaluate and analyze the massive data generated by series of microarray experiments is of utmost importance to reveal the hidden patterns of gene expressio...
Junbai Wang, Jan Delabie, Hans Christian Aasheim, ...
BMCBI
2006
213views more  BMCBI 2006»
14 years 9 months ago
CoXpress: differential co-expression in gene expression data
Background: Traditional methods of analysing gene expression data often include a statistical test to find differentially expressed genes, or use of a clustering algorithm to find...
Michael Watson
DASFAA
2005
IEEE
137views Database» more  DASFAA 2005»
15 years 3 months ago
A General Approach to Mining Quality Pattern-Based Clusters from Microarray Data
Abstract. Pattern-based clustering has broad applications in microarray data analysis, customer segmentation, e-business data analysis, etc. However, pattern-based clustering often...
Daxin Jiang, Jian Pei, Aidong Zhang
BMCBI
2006
118views more  BMCBI 2006»
14 years 9 months ago
Statistical analysis of an RNA titration series evaluates microarray precision and sensitivity on a whole-array basis
Background: Concerns are often raised about the accuracy of microarray technologies and the degree of cross-platform agreement, but there are yet no methods which can unambiguousl...
Andrew J. Holloway, Alicia Oshlack, Dileepa S. Diy...
CIKM
2004
Springer
15 years 2 months ago
Mining gene expression datasets using density-based clustering
Given the recent advancement of microarray technologies, we present a density-based clustering approach for the purpose of co-expressed gene cluster identification. The underlyin...
Seokkyung Chung, Jongeun Jun, Dennis McLeod