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» Mining Spatial Gene Expression Data for Association Rules
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BIRD
2007
Springer
154views Bioinformatics» more  BIRD 2007»
13 years 10 months ago
Mining Spatial Gene Expression Data for Association Rules
Abstract. We analyse data from the Edinburgh Mouse Atlas GeneExpression Database (EMAGE) which is a high quality data source for spatio-temporal gene expression patterns. Using a n...
Jano I. van Hemert, Richard A. Baldock
KDD
2003
ACM
190views Data Mining» more  KDD 2003»
14 years 4 months ago
Distance-enhanced association rules for gene expression
We introduce a novel data mining technique for the analysis of gene expression. Gene expression is the effective production of the protein that a gene encodes. We focus on the cha...
Aleksandar Icev, Carolina Ruiz, Elizabeth F. Ryder
BMCBI
2006
109views more  BMCBI 2006»
13 years 4 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...
VLDB
2004
ACM
115views Database» more  VLDB 2004»
13 years 9 months ago
Semantic Mining and Analysis of Gene Expression Data
Association rules can reveal biological relevant relationship between genes and environments / categories. However, most existing association rule mining algorithms are rendered i...
Xin Xu, Gao Cong, Beng Chin Ooi, Kian-Lee Tan, Ant...