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» A stable gene selection in microarray data analysis
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BMCBI
2008
128views more  BMCBI 2008»
13 years 8 months ago
Improving the prediction accuracy in classification using the combined data sets by ranks of gene expressions
Background: The information from different data sets experimented under different conditions may be inconsistent even though they are performed with the same research objectives. ...
Ki-Yeol Kim, Dong Hyuk Ki, Hei-Cheul Jeung, Hyun C...
BIBE
2004
IEEE
107views Bioinformatics» more  BIBE 2004»
13 years 11 months ago
Enhanced pClustering and Its Applications to Gene Expression Data
Clustering has been one of the most popular methods to discover useful biological insights from DNA microarray. An interesting paradigm is simultaneous clustering of both genes an...
Sungroh Yoon, Christine Nardini, Luca Benini, Giov...
JIB
2006
110views more  JIB 2006»
13 years 7 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...
ESANN
2008
13 years 9 months ago
A method for robust variable selection with significance assessment
Our goal is proposing an unbiased framework for gene expression analysis based on variable selection combined with a significance assessment step. We start by discussing the need ...
Annalisa Barla, Sofia Mosci, Lorenzo Rosasco, Ales...
BMCBI
2008
105views more  BMCBI 2008»
13 years 8 months ago
SIGMA2: A system for the integrative genomic multi-dimensional analysis of cancer genomes, epigenomes, and transcriptomes
Background: High throughput microarray technologies have afforded the investigation of genomes, epigenomes, and transcriptomes at unprecedented resolution. However, software packa...
Raj Chari, Bradley P. Coe, Craig Wedseltoft, Marie...