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» A stable gene selection in microarray data analysis
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IDEAL
2005
Springer
14 years 1 months ago
A Comparative Study of Two Novel Predictor Set Scoring Methods
Due to the large number of genes measured in a typical microarray dataset, feature selection plays an essential role in tumor classification. In turn, relevance and redundancy are ...
Chia Huey Ooi, Madhu Chetty
BMCBI
2006
213views more  BMCBI 2006»
13 years 7 months ago
CoXpress: differential co-expression in gene expression data
Background: Traditional methods of analysing gene expression data often include a statistical test to find differentially expressed genes, or use of a clustering algorithm to find...
Michael Watson
BMCBI
2010
129views more  BMCBI 2010»
13 years 7 months ago
A temporal precedence based clustering method for gene expression microarray data
Background: Time-course microarray experiments can produce useful data which can help in understanding the underlying dynamics of the system. Clustering is an important stage in m...
Ritesh Krishna, Chang-Tsun Li, Vicky Buchanan-Woll...
IJCSA
2007
98views more  IJCSA 2007»
13 years 7 months ago
Extracted Knowledge Interpretation in mining biological data: a survey
This paper discusses different approaches for integrating biological knowledge in gene expression analysis. Indeed we are interested in the fifth step of microarray analysis pro...
Martine Collard, Ricardo Martínez
BMCBI
2006
100views more  BMCBI 2006»
13 years 7 months ago
Chromosomal patterns of gene expression from microarray data: methodology, validation and clinical relevance in gliomas
Background: Expression microarrays represent a powerful technique for the simultaneous investigation of thousands of genes. The evidence that genes are not randomly distributed in...
Federico E. Turkheimer, Federico Roncaroli, Benoit...