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» Clustering Genes Using Heterogeneous Data Sources
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APBC
2004
138views Bioinformatics» more  APBC 2004»
14 years 11 days ago
Whole-Genome Functional Classification of Genes by Latent Semantic Analysis on Microarray Data
Quantitative simultaneous monitoring of the expression levels of thousands of genes under various experimental conditions is now possible using microarray experiments. The resulti...
See-Kiong Ng, Zexuan Zhu, Yew-Soon Ong
ICTAI
2003
IEEE
14 years 4 months ago
Integrating Microarray Data by Consensus Clustering
With the exploding volume of microarray experiments comes increasing interest in mining repositories of such data. Meaningfully combining results from varied experiments on an equ...
Vladimir Filkov, Steven Skiena
ICDM
2010
IEEE
226views Data Mining» more  ICDM 2010»
13 years 9 months ago
Edge Weight Regularization over Multiple Graphs for Similarity Learning
The growth of the web has directly influenced the increase in the availability of relational data. One of the key problems in mining such data is computing the similarity between o...
Pradeep Muthukrishnan, Dragomir R. Radev, Qiaozhu ...
BMCBI
2006
109views more  BMCBI 2006»
13 years 11 months ago
Integrated analysis of gene expression by association rules discovery
Background: Microarray technology is generating huge amounts of data about the expression level of thousands of genes, or even whole genomes, across different experimental conditi...
Pedro Carmona-Saez, Monica Chagoyen, Andrés...
BMCBI
2008
178views more  BMCBI 2008»
13 years 11 months ago
Identification of coherent patterns in gene expression data using an efficient biclustering algorithm and parallel coordinate vi
Background: The DNA microarray technology allows the measurement of expression levels of thousands of genes under tens/hundreds of different conditions. In microarray data, genes ...
Kin-On Cheng, Ngai-Fong Law, Wan-Chi Siu, Alan Wee...