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May 2017 Issue Vol.7 No.5
Analysis of Microarray Gene Expression
Data Using Boolean Association Rule Mining
https://ia601503.us.archive.org/13/items/vol7no05/vol7no05.pdf
R. Vengateshkumar
Research Scholar, Research & Development center,Bharathiar University, Coimbatore,Tamil Nadu, India
S. Alagukumar
Assistant Professor, Department of Computer Applications,Ayya Nadar Janaki Ammal College, Sivakasi,Tamil Nadu, India
Dr.R. Lawrance
Director, Department of Computer Applications,Ayya Nadar Janaki Ammal College, Sivakasi, Tamil Nadu, India
Abstract:
Data Mining is one of the interdisciplinary fieldson the research area. Association rule mining plays a vital
role in the data mining for finding significant relations in biological data. Microarray technology is mainly used by
the researchers to find the meaningful relations among gene expression data. In this research paper, the
statistical t-test has been applied to select the significant genes, equal frequency binning method has been
implemented for discretizing the gene expression data,Boolean Association Rules (BAR) generate the frequent
gene expression intervals and finally, the association rules has been discovered. Association rules discover the
significant relations among microarray gene expression data. It exposes the correlation among the gene
expression and used to provide the significant decision for cancer diagnosis.
Keywords:Microarray, Gene Filtering, Equal Frequency,Frequent Pattern Mining and Association Rule Mining.
