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» Microarray Gene Expression Data Analysis
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BMCBI
2011
14 years 1 months ago
Gene set analysis for longitudinal gene expression data
Background: Gene set analysis (GSA) has become a successful tool to interpret gene expression profiles in terms of biological functions, molecular pathways, or genomic locations. ...
Ke Zhang, Haiyan Wang, Arne C. Bathke, Solomon W. ...
BMCBI
2005
153views more  BMCBI 2005»
14 years 9 months ago
Mining published lists of cancer related microarray experiments: Identification of a gene expression signature having a critical
Background: Routine application of gene expression microarray technology is rapidly producing large amounts of data that necessitate new approaches of analysis. The analysis of a ...
Giacomo Finocchiaro, Francesco Mancuso, Heiko M&uu...
JIFS
2002
134views more  JIFS 2002»
14 years 9 months ago
Classification of gene expression data using fuzzy logic
Microarray technologies have allowed the measurement of expression of multiple genes simultaneously. Gene expression levels can be used to classify tissues into diagnostic or progn...
Lucila Ohno-Machado, Staal A. Vinterbo, Griffin We...
JCB
2002
93views more  JCB 2002»
14 years 9 months ago
Unfolding of Microarray Data
The use of DNA microarrays for the analysis of complex biological samples is becoming a mainstream part of biomedical research. One of the most commonly used methods compares the ...
Andrew B. Goryachev, Pascale F. Macgregor, Aled M....
BMCBI
2011
14 years 1 months ago
Evaluating methods for ranking differentially expressed genes applied to MicroArray Quality Control data
Background: Statistical methods for ranking differentially expressed genes (DEGs) from gene expression data should be evaluated with regard to high sensitivity, specificity, and r...
Koji Kadota, Kentaro Shimizu