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ISNN
2005
Springer
14 years 1 months ago
Non-parametric Statistical Tests for Informative Gene Selection
This paper presents two non-parametric statistical test methods, called Kolmogorov-Smirnov (KS) and U statistic test methods, respectively, for informative gene selection of a tumo...
Jinwen Ma, Fuhai Li, Jianfeng Liu
BMCBI
2010
167views more  BMCBI 2010»
13 years 7 months ago
Bi-directional gene set enrichment and canonical correlation analysis identify key diet-sensitive pathways and biomarkers of met
Background: Currently, a number of bioinformatics methods are available to generate appropriate lists of genes from a microarray experiment. While these lists represent an accurat...
Melissa J. Morine, Jolene McMonagle, Sinead Toomey...
BMCBI
2008
157views more  BMCBI 2008»
13 years 7 months ago
Dimension reduction with redundant gene elimination for tumor classification
Background: Analysis of gene expression data for tumor classification is an important application of bioinformatics methods. But it is hard to analyse gene expression data from DN...
Xue-Qiang Zeng, Guo-Zheng Li, Jack Y. Yang, Mary Q...
BMCBI
2004
115views more  BMCBI 2004»
13 years 7 months ago
Quantifying the relationship between co-expression, co-regulation and gene function
Background: It is thought that genes with similar patterns of mRNA expression and genes with similar functions are likely to be regulated via the same mechanisms. It has been diff...
Dominic J. Allocco, Isaac S. Kohane, Atul J. Butte
BMCBI
2004
158views more  BMCBI 2004»
13 years 7 months ago
Incremental genetic K-means algorithm and its application in gene expression data analysis
Background: In recent years, clustering algorithms have been effectively applied in molecular biology for gene expression data analysis. With the help of clustering algorithms suc...
Yi Lu, Shiyong Lu, Farshad Fotouhi, Youping Deng, ...