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» Evaluation of clustering algorithms for gene expression data
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WCE
2007
15 years 2 months ago
Gene Selection for Tumor Classification Using Microarray Gene Expression Data
– In this paper we perform a t-test for significant gene expression analysis in different dimensions based on molecular profiles from microarray data, and compare several computa...
Krishna Yendrapalli, Ram B. Basnet, Srinivas Mukka...
ALMOB
2008
93views more  ALMOB 2008»
15 years 1 months ago
A weighted average difference method for detecting differentially expressed genes from microarray data
Background: Identification of differentially expressed genes (DEGs) under different experimental conditions is an important task in many microarray studies. However, choosing whic...
Koji Kadota, Yuji Nakai, Kentaro Shimizu
ISBI
2006
IEEE
16 years 2 months ago
Clustering gene expression patterns of fly embryos
The spatio-temporal patterning of gene expression in early embryos is an important source of information for understanding the functions of genes involved in development. Most ana...
Hanchuan Peng, Fuhui Long, Michael B. Eisen, Eugen...
CBMS
2005
IEEE
15 years 7 months ago
An Ontology-Driven Clustering Method for Supporting Gene Expression Analysis
The Gene Ontology (GO) is an important knowledge resource for biologists and bioinformaticians. This paper explores the integration of similarity information derived from GO into ...
Haiying Wang, Francisco Azuaje, Olivier Bodenreide...
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BTW
2003
Springer
94views Database» more  BTW 2003»
15 years 6 months ago
Comparative Evaluation of Microarray-based Gene Expression Databases
Microarrays make it possible to monitor the expression of thousands of genes in parallel thus generating huge amounts of data. So far, several databases have been developed for man...
Hong Hai Do, Toralf Kirsten, Erhard Rahm