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» Extracting and Explaining Biological Knowledge in Microarray...
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82
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BMCBI
2010
130views more  BMCBI 2010»
14 years 9 months ago
Knowledge-guided gene ranking by coordinative component analysis
Background: In cancer, gene networks and pathways often exhibit dynamic behavior, particularly during the process of carcinogenesis. Thus, it is important to prioritize those gene...
Chen Wang, Jianhua Xuan, Huai Li, Yue Wang, Ming Z...
BMCBI
2008
138views more  BMCBI 2008»
14 years 9 months ago
M-BISON: Microarray-based integration of data sources using networks
Background: The accurate detection of differentially expressed (DE) genes has become a central task in microarray analysis. Unfortunately, the noise level and experimental variabi...
Bernie J. Daigle Jr., Russ B. Altman
94
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BMCBI
2004
150views more  BMCBI 2004»
14 years 9 months ago
Rank Difference Analysis of Microarrays (RDAM), a novel approach to statistical analysis of microarray expression profiling data
Background: A key step in the analysis of microarray expression profiling data is the identification of genes that display statistically significant changes in expression signals ...
Dietmar E. Martin, Philippe Demougin, Michael N. H...
80
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JIB
2006
110views more  JIB 2006»
14 years 9 months ago
Combining biomedical knowledge and transcriptomic data to extract new knowledge on genes
In biomedical research, interpretation of microarray data requires confrontation of data and knowledge from heterogeneous resources, either in the biomedical domain or in genomics...
Emilie Guérin, Gwenaëlle Marquet, Juli...
97
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BIBM
2007
IEEE
171views Bioinformatics» more  BIBM 2007»
15 years 4 months ago
GenMiner: Mining Informative Association Rules from Genomic Data
GENMINER is a smart adaptation of closed itemsets based association rules extraction to genomic data. It takes advantage of the novel NORDI discretization method and of the CLOSE ...
Ricardo Martínez, Claude Pasquier, Nicolas ...