Mining Association Rules from Signals found in Mammalian Promoter Sequences

Gen Shibayama (gengen@ims.u-tokyo.ac.jp)
Kenji Satou (ken@ims.u-tokyo.ac.jp)
Toshihisa Takagi(takagi@ims.u-tokyo.ac.jp)

Human Genome Center, Institute of Medical Science, The University of Tokyo
Shiroganedai, Minato-ku, Tokyo 108, Japan

Abstract

To find associations among large amount of genome data, we implemented a data mining algorithm developed by Houtsma et al. As the result of a computer experiment about signals found in mammalian promoter sequences, the system generated association rules with high accuracy and large coverage.