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DILS
2005
Springer
14 years 1 months ago
Integrating Heterogeneous Microarray Data Sources Using Correlation Signatures
Abstract. Microarrays are one of the latest breakthroughs in experimental molecular biology. Thousands of different research groups generate tens of thousands of microarray gene e...
Jaewoo Kang, Jiong Yang, Wanhong Xu, Pankaj Chopra
BMCBI
2005
80views more  BMCBI 2005»
13 years 7 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
BMCBI
2005
112views more  BMCBI 2005»
13 years 7 months ago
Visualization methods for statistical analysis of microarray clusters
Background: The most common method of identifying groups of functionally related genes in microarray data is to apply a clustering algorithm. However, it is impossible to determin...
Matthew A. Hibbs, Nathaniel C. Dirksen, Kai Li, Ol...
BMCBI
2007
149views more  BMCBI 2007»
13 years 7 months ago
A unified framework for finding differentially expressed genes from microarray experiments
Background: This paper presents a unified framework for finding differentially expressed genes (DEGs) from the microarray data. The proposed framework has three interrelated modul...
Jahangheer S. Shaik, Mohammed Yeasin
BMCBI
2008
173views more  BMCBI 2008»
13 years 7 months ago
Gene Vector Analysis (Geneva): A unified method to detect differentially-regulated gene sets and similar microarray experiments
Background: Microarray experiments measure changes in the expression of thousands of genes. The resulting lists of genes with changes in expression are then searched for biologica...
Stephen W. Tanner, Pankaj Agarwal