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» Mining Spatial Gene Expression Data for Association Rules
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GIS
2005
ACM
14 years 8 months ago
Extracting spatial association rules from spatial transactions
Georeferenced information is growing every day, and geographical information systems are becoming crucial in many decision processes. As a consequence, extracting knowledge from G...
Salvatore Rinzivillo, Franco Turini
DSS
2007
127views more  DSS 2007»
13 years 7 months ago
Large-scale regulatory network analysis from microarray data: modified Bayesian network learning and association rule mining
We present two algorithms for learning large-scale gene regulatory networks from microarray data: a modified informationtheory-based Bayesian network algorithm and a modified asso...
Zan Huang, Jiexun Li, Hua Su, George S. Watts, Hsi...
BMCBI
2006
155views more  BMCBI 2006»
13 years 7 months ago
AffyMiner: mining differentially expressed genes and biological knowledge in GeneChip microarray data
Background: DNA microarrays are a powerful tool for monitoring the expression of tens of thousands of genes simultaneously. With the advance of microarray technology, the challeng...
Guoqing Lu, The V. Nguyen, Yuannan Xia, Michael Fr...
BMCBI
2008
171views more  BMCBI 2008»
13 years 7 months ago
Fuzzy association rules for biological data analysis: A case study on yeast
Background: Last years' mapping of diverse genomes has generated huge amounts of biological data which are currently dispersed through many databases. Integration of the info...
Francisco J. Lopez, Armando Blanco, Fernando Garci...
ICANN
2009
Springer
13 years 5 months ago
Mining Rules for the Automatic Selection Process of Clustering Methods Applied to Cancer Gene Expression Data
Different algorithms have been proposed in the literature to cluster gene expression data, however there is no single algorithm that can be considered the best one independently on...
André C. A. Nascimento, Ricardo Bastos Cava...