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» A Repulsive Clustering Algorithm for Gene Expression Data
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BMCBI
2005
80views more  BMCBI 2005»
13 years 9 months ago
Sample phenotype clusters in high-density oligonucleotide microarray data sets are revealed using Isomap, a nonlinear algorithm
Background: Life processes are determined by the organism's genetic profile and multiple environmental variables. However the interaction between these factors is inherently ...
Kevin Dawson, Raymond L. Rodriguez, Wasyl Malyj
BIBM
2009
IEEE
172views Bioinformatics» more  BIBM 2009»
14 years 2 months ago
Identifying Gene Signatures from Cancer Progression Data Using Ordinal Analysis
—A comprehensive understanding of cancer progression may shed light on genetic and molecular mechanisms of oncogenesis, and it may provide much needed information for effective d...
Yoon Soo Pyon, Jing Li
BMCBI
2007
112views more  BMCBI 2007»
13 years 9 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...
CSB
2004
IEEE
106views Bioinformatics» more  CSB 2004»
14 years 23 days ago
A Theoretical Analysis of Gene Selection
A great deal of recent research has focused on the challenging task of selecting differentially expressed genes from microarray data (`gene selection'). Numerous gene selecti...
Sach Mukherjee, Stephen J. Roberts
ICASSP
2009
IEEE
14 years 3 months ago
Robust cross-race gene expression analysis
This paper develops a Bayesian network (BN) predictor to profile cross-race gene expression data. Cross-race studies face more data variability than single-lab studies. Our desig...
Hsun-Hsien Chang, Marco Ramoni