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» E-CAST: A Data Mining Algorithm for Gene Expression Data
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BMCBI
2010
97views more  BMCBI 2010»
13 years 6 months ago
Preprocessing of gene expression data by optimally robust estimators
Background: The preprocessing of gene expression data obtained from several platforms routinely includes the aggregation of multiple raw signal intensities to one expression value...
Matthias Kohl, Hans-Peter Deigner
BMCBI
2011
13 years 17 days ago
Clustering gene expression data with a penalized graph-based metric
Background: The search for cluster structure in microarray datasets is a base problem for the so-called “-omic sciences”. A difficult problem in clustering is how to handle da...
Ariel E. Bayá, Pablo M. Granitto
CSB
2003
IEEE
130views Bioinformatics» more  CSB 2003»
14 years 2 months ago
Latent Structure Models for the Analysis of Gene Expression Data
Cluster methods have been successfully applied in gene expression data analysis to address tumor classification. By grouping tissue samples into homogeneous subsets, more systema...
Dong Hua, Dechang Chen, Xiuzhen Cheng, Abdou Youss...
BIBE
2007
IEEE
153views Bioinformatics» more  BIBE 2007»
13 years 10 months ago
Combined expression data with missing values and gene interaction network analysis: a Markovian integrated approach
—DNA microarray technologies provide means for monitoring in the order of tens of thousands of gene expression levels quantitatively and simultaneously. However data generated in...
Juliette Blanchet, Matthieu Vignes
IDEAL
2004
Springer
14 years 2 months ago
Visualisation of Distributions and Clusters Using ViSOMs on Gene Expression Data
Microarray datasets are often too large to visualise due to the high dimensionality. The self-organising map has been found useful to analyse massive complex datasets. It can be us...
Swapna Sarvesvaran, Hujun Yin