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» Mining Spatial Gene Expression Data for Association Rules
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BMCBI
2008
161views more  BMCBI 2008»
14 years 11 months ago
Inferring gene expression dynamics via functional regression analysis
Background: Temporal gene expression profiles characterize the time-dynamics of expression of specific genes and are increasingly collected in current gene expression experiments....
Hans-Georg Müller, Jeng-Min Chiou, Xiaoyan Le...
97
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DATAMINE
2000
115views more  DATAMINE 2000»
14 years 11 months ago
Integrating Association Rule Mining with Relational Database Systems: Alternatives and Implications
Data mining on large data warehouses is becoming increasingly important. In support of this trend, we consider a spectrum of architectural alternatives for coupling mining with da...
Sunita Sarawagi, Shiby Thomas, Rakesh Agrawal
BMCBI
2006
144views more  BMCBI 2006»
14 years 11 months ago
Association algorithm to mine the rules that govern enzyme definition and to classify protein sequences
Background: The number of sequences compiled in many genome projects is growing exponentially, but most of them have not been characterized experimentally. An automatic annotation...
Shih-Hau Chiu, Chien-Chi Chen, Gwo-Fang Yuan, Thy-...
207
Voted
ICDE
1995
IEEE
139views Database» more  ICDE 1995»
16 years 1 months ago
Set-Oriented Mining for Association Rules in Relational Databases
We describe set-oriented algorithms for mining association rules. Such algorithms imply performing multiple joins and may appear to be inherently less escient than special-purpose...
Maurice A. W. Houtsma, Arun N. Swami
BMCBI
2004
135views more  BMCBI 2004»
14 years 11 months ago
Determination of the differentially expressed genes in microarray experiments using local FDR
Background: Thousands of genes in a genomewide data set are tested against some null hypothesis, for detecting differentially expressed genes in microarray experiments. The expect...
Julie Aubert, Avner Bar-Hen, Jean-Jacques Daudin, ...