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» The ParTriCluster Algorithm for Gene Expression Analysis
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113
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BMCBI
2006
153views more  BMCBI 2006»
15 years 17 days ago
Cancer diagnosis marker extraction for soft tissue sarcomas based on gene expression profiling data by using projective adaptive
Background: Recent advances in genome technologies have provided an excellent opportunity to determine the complete biological characteristics of neoplastic tissues, resulting in ...
Hiro Takahashi, Takeshi Nemoto, Teruhiko Yoshida, ...
IJCNN
2008
IEEE
15 years 7 months ago
Comparative study on normalization procedures for cluster analysis of gene expression datasets
—Normalization before clustering is often needed for proximity indices, such as Euclidian distance, which are sensitive to differences in the magnitude or scales of the attribute...
Marcílio Carlos Pereira de Souto, Daniel S....
96
Voted
CSB
2005
IEEE
146views Bioinformatics» more  CSB 2005»
15 years 6 months ago
Multi-Metric and Multi-Substructure Biclustering Analysis for Gene Expression Data
A good number of biclustering algorithms have been proposed for grouping gene expression data. Many of them have adopted matrix norms to define the similarity score of a bicluste...
Sun-Yuan Kung, Man-Wai Mak, Ilias Tagkopoulos
CSB
2003
IEEE
130views Bioinformatics» more  CSB 2003»
15 years 5 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»
15 years 2 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