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» Improving gene set analysis of microarray data by SAM-GS
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BMCBI
2006
116views more  BMCBI 2006»
13 years 7 months ago
Integrative missing value estimation for microarray data
Background: Missing value estimation is an important preprocessing step in microarray analysis. Although several methods have been developed to solve this problem, their performan...
Jianjun Hu, Haifeng Li, Michael S. Waterman, Xiang...
BMCBI
2007
143views more  BMCBI 2007»
13 years 7 months ago
Gene selection for classification of microarray data based on the Bayes error
Background: With DNA microarray data, selecting a compact subset of discriminative genes from thousands of genes is a critical step for accurate classification of phenotypes for, ...
Ji-Gang Zhang, Hong-Wen Deng
WILF
2007
Springer
147views Fuzzy Logic» more  WILF 2007»
14 years 1 months ago
Fuzzy Ensemble Clustering for DNA Microarray Data Analysis
Two major problems related the unsupervised analysis of gene expression data are represented by the accuracy and reliability of the discovered clusters, and by the biological fact ...
Roberto Avogadri, Giorgio Valentini
BMCBI
2006
165views more  BMCBI 2006»
13 years 7 months ago
A stable gene selection in microarray data analysis
Background: Microarray data analysis is notorious for involving a huge number of genes compared to a relatively small number of samples. Gene selection is to detect the most signi...
Kun Yang, Zhipeng Cai, Jianzhong Li, Guohui Lin