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BMCBI
2006
164views more  BMCBI 2006»
13 years 7 months ago
Evaluation of clustering algorithms for gene expression data
Background: Cluster analysis is an integral part of high dimensional data analysis. In the context of large scale gene expression data, a filtered set of genes are grouped togethe...
Susmita Datta, Somnath Datta
BMCBI
2006
142views more  BMCBI 2006»
13 years 7 months ago
Improving the Performance of SVM-RFE to Select Genes in Microarray Data
Background: Recursive Feature Elimination is a common and well-studied method for reducing the number of attributes used for further analysis or development of prediction models. ...
Yuanyuan Ding, Dawn Wilkins
BMCBI
2010
193views more  BMCBI 2010»
13 years 2 months ago
Mayday - integrative analytics for expression data
Background: DNA Microarrays have become the standard method for large scale analyses of gene expression and epigenomics. The increasing complexity and inherent noisiness of the ge...
Florian Battke, Stephan Symons, Kay Nieselt
BMCBI
2008
123views more  BMCBI 2008»
13 years 7 months ago
Pol II promoter prediction using characteristic 4-mer motifs: a machine learning approach
Background: Eukaryotic promoter prediction using computational analysis techniques is one of the most difficult jobs in computational genomics that is essential for constructing a...
Firoz Anwar, Syed Murtuza Baker, Taskeed Jabid, Md...
BMCBI
2010
214views more  BMCBI 2010»
13 years 7 months ago
AutoSOME: a clustering method for identifying gene expression modules without prior knowledge of cluster number
Background: Clustering the information content of large high-dimensional gene expression datasets has widespread application in "omics" biology. Unfortunately, the under...
Aaron M. Newman, James B. Cooper