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» A Repulsive Clustering Algorithm for Gene Expression Data
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BMCBI
2005
151views more  BMCBI 2005»
13 years 9 months ago
stam - a Bioconductor compliant R package for structured analysis of microarray data
Background: Genome wide microarray studies have the potential to unveil novel disease entities. Clinically homogeneous groups of patients can have diverse gene expression profiles...
Claudio Lottaz, Rainer Spang
CMSB
2006
Springer
14 years 24 days ago
Possibilistic Approach to Biclustering: An Application to Oligonucleotide Microarray Data Analysis
Abstract. The important research objective of identifying genes with similar behavior with respect to different conditions has recently been tackled with biclustering techniques. I...
Maurizio Filippone, Francesco Masulli, Stefano Rov...
DILS
2004
Springer
14 years 2 months ago
Heterogeneous Data Integration with the Consensus Clustering Formalism
Meaningfully integrating massive multi-experimental genomic data sets is becoming critical for the understanding of gene function. We have recently proposed methodologies for integ...
Vladimir Filkov, Steven Skiena
ESANN
2008
13 years 10 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...
PRL
2006
130views more  PRL 2006»
13 years 9 months ago
Efficient huge-scale feature selection with speciated genetic algorithm
With increasing interest in bioinformatics, sophisticated tools are required to efficiently analyze gene information. The classification of gene expression profiles is crucial in ...
Jin-Hyuk Hong, Sung-Bae Cho