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BMCBI
2006
114views more  BMCBI 2006»
13 years 10 months ago
Empirical validation of the S-Score algorithm in the analysis of gene expression data
Background: Current methods of analyzing Affymetrix GeneChip
Richard E. Kennedy, Kellie J. Archer, Michael F. M...
PRIB
2009
Springer
147views Bioinformatics» more  PRIB 2009»
14 years 4 months ago
Cross-Platform Analysis with Binarized Gene Expression Data
Abstract. With widespread use of microarray technology as a potential diagnostics tool, the comparison of results obtained from the use of different platforms is of interest. When...
Salih Tuna, Mahesan Niranjan
CSB
2004
IEEE
136views Bioinformatics» more  CSB 2004»
14 years 1 months ago
Minimum Entropy Clustering and Applications to Gene Expression Analysis
Clustering is a common methodology for analyzing the gene expression data. In this paper, we present a new clustering algorithm from an information-theoretic point of view. First,...
Haifeng Li, Keshu Zhang, Tao Jiang
BIOINFORMATICS
2004
119views more  BIOINFORMATICS 2004»
13 years 9 months ago
Analysis of variance components in gene expression data
Motivation: A microarray experiment is a multi-step process, and each step is a potential source of variation. There are two major sources of variation: biological variation and t...
James J. Chen, Robert R. Delongchamp, Chen-An Tsai...
BMCBI
2005
154views more  BMCBI 2005»
13 years 10 months ago
GObar: A Gene Ontology based analysis and visualization tool for gene sets
Background: Microarray experiments, as well as other genomic analyses, often result in large gene sets containing up to several hundred genes. The biological significance of such ...
Jason S. M. Lee, Gurpreet Katari, Ravi Sachidanand...