Title :
Strong Association Rules Mining Without Using Frequent Items for Microarray Analysis
Author :
Wang, Miao ; Shang, Xuequn ; Zhao, Qian ; Li, Zhanhuai
Author_Institution :
Sch. of Comput. Sci. & Eng., Northwestern Polytech. Univ., Xian, China
Abstract :
Microarray technology has created a revolution in the field of biological research. Association rules can not only group the similarly expressed genes but also discern relationships among genes. However, the efficiency of traditional method to generate association rules is not very well. We develop a novel algorithm, SAW, to generate strong association rules by combining the paired rules, which can avoid lots of unnecessary computing that traditional method often encounter. The experiments show our method is more efficiently than FARMER.
Keywords :
biology computing; data mining; genetics; association rules mining; expressed genes; frequent pattern mining; microarray analysis; paired rules; Aging; Association rules; Biological processes; Computer science; Data analysis; Data mining; Electronic mail; Gene expression; Protein engineering; Surface acoustic waves;
Conference_Titel :
Bioinformatics and Biomedical Engineering , 2009. ICBBE 2009. 3rd International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-2901-1
Electronic_ISBN :
978-1-4244-2902-8
DOI :
10.1109/ICBBE.2009.5163431