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» Unfolding of Microarray Data
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BIBE
2004
IEEE
120views Bioinformatics» more  BIBE 2004»
13 years 11 months ago
Identifying Projected Clusters from Gene Expression Profiles
In microarray gene expression data, clusters may hide in subspaces. Traditional clustering algorithms that make use of similarity measurements in the full input space may fail to ...
Kevin Y. Yip, David W. Cheung, Michael K. Ng, Kei-...
HIS
2008
13 years 9 months ago
CBR System for Diagnosis of Patients
Microarray technology allows to measure the expression levels of thousands of genes in an experiment. The use of computational methods is fundamental in cancer research. One of th...
Juan Francisco de Paz, Sara Rodríguez, Javi...
BMCBI
2007
112views more  BMCBI 2007»
13 years 8 months ago
Selecting dissimilar genes for multi-class classification, an application in cancer subtyping
Background: Gene expression microarray is a powerful technology for genetic profiling diseases and their associated treatments. Such a process involves a key step of biomarker ide...
Zhipeng Cai, Randy Goebel, Mohammad R. Salavatipou...
BIBE
2003
IEEE
128views Bioinformatics» more  BIBE 2003»
14 years 1 months ago
A Repulsive Clustering Algorithm for Gene Expression Data
: - Facing the development of microarray technology, clustering is currently a leading technique to gene expression data analysis. In this paper, we propose a novel algorithm calle...
Chyun-Shin Cheng, Shiuan-Sz Wang
BMCBI
2006
81views more  BMCBI 2006»
13 years 8 months ago
A fisheye viewer for microarray-based gene expression data
Background: Microarray has been widely used to measure the relative amounts of every mRNA transcript from the genome in a single scan. Biologists have been accustomed to reading t...
Min Wu, Cheng Thao, Xiangming Mu, Ethan V. Munson