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BMCBI
2006
183views more  BMCBI 2006»
13 years 8 months ago
Mining gene expression data by interpreting principal components
Background: There are many methods for analyzing microarray data that group together genes having similar patterns of expression over all conditions tested. However, in many insta...
Joseph C. Roden, Brandon W. King, Diane Trout, Ali...
KES
2005
Springer
14 years 1 months ago
Bayesian Validation of Fuzzy Clustering for Analysis of Yeast Cell Cycle Data
Clustering for the analysis of the gene expression profiles has been used for identifying the functions of the genes and of unknown genes. Since the genes usually belong to multipl...
Kyung-Joong Kim, Si-Ho Yoo, Sung-Bae Cho
BMCBI
2008
178views more  BMCBI 2008»
13 years 8 months ago
Identification of coherent patterns in gene expression data using an efficient biclustering algorithm and parallel coordinate vi
Background: The DNA microarray technology allows the measurement of expression levels of thousands of genes under tens/hundreds of different conditions. In microarray data, genes ...
Kin-On Cheng, Ngai-Fong Law, Wan-Chi Siu, Alan Wee...
BMCBI
2010
155views more  BMCBI 2010»
13 years 8 months ago
A bi-ordering approach to linking gene expression with clinical annotations in gastric cancer
Background: In the study of cancer genomics, gene expression microarrays, which measure thousands of genes in a single assay, provide abundant information for the investigation of...
Fan Shi, Christopher Leckie, Geoff MacIntyre, Izha...
BIBM
2009
IEEE
172views Bioinformatics» more  BIBM 2009»
14 years 1 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