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» Mining Spatial Gene Expression Data for Association Rules
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KDD
2002
ACM
150views Data Mining» more  KDD 2002»
16 years 2 days ago
Querying multiple sets of discovered rules
Rule mining is an important data mining task that has been applied to numerous real-world applications. Often a rule mining system generates a large number of rules and only a sma...
Alexander Tuzhilin, Bing Liu
BICOB
2009
Springer
14 years 9 months ago
A Biclustering Method to Discover Co-regulated Genes Using Diverse Gene Expression Datasets
We propose a two-step biclustering approach to mine co-regulation patterns of a given reference gene to discover other genes that function in a common biological process. Currently...
Doruk Bozdag, Jeffrey D. Parvin, Ümit V. &Cce...
AAI
2007
132views more  AAI 2007»
14 years 11 months ago
Incremental Extraction of Association Rules in Applicative Domains
In recent years, the KDD process has been advocated to be an iterative and interactive process. It is seldom the case that a user is able to answer immediately with a single query...
Arianna Gallo, Roberto Esposito, Rosa Meo, Marco B...
ECAI
2004
Springer
15 years 5 months ago
Exploiting Association and Correlation Rules - Parameters for Improving the K2 Algorithm
A Bayesian network is an appropriate tool to deal with the uncertainty that is typical of real-life applications. Bayesian network arcs represent statistical dependence between dif...
Evelina Lamma, Fabrizio Riguzzi, Sergio Storari
KDD
2009
ACM
249views Data Mining» more  KDD 2009»
16 years 7 days ago
Drosophila gene expression pattern annotation using sparse features and term-term interactions
The Drosophila gene expression pattern images document the spatial and temporal dynamics of gene expression and they are valuable tools for explicating the gene functions, interac...
Shuiwang Ji, Lei Yuan, Ying-Xin Li, Zhi-Hua Zhou, ...