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» Mining Spatial Gene Expression Data for Association Rules
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BMCBI
2008
161views more  BMCBI 2008»
15 years 2 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...
DATAMINE
2000
115views more  DATAMINE 2000»
15 years 1 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»
15 years 1 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-...
ICDE
1995
IEEE
139views Database» more  ICDE 1995»
16 years 3 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
126
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BMCBI
2004
135views more  BMCBI 2004»
15 years 1 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, ...