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» Mining Spatial Gene Expression Data for Association Rules
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76
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BIRD
2007
Springer
154views Bioinformatics» more  BIRD 2007»
15 years 3 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
79
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KDD
2003
ACM
190views Data Mining» more  KDD 2003»
15 years 10 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»
14 years 9 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»
15 years 2 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...