Mining of Correlated Rules in Genome Sequences

• Main Authors: Lin, L., Wong, L., Tze-Yun LEONG, Lai, P. S.
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2002
• Subjects: Computer Sciences; Databases and Information Systems; Genetics and Genomics; Health Information Technology; Numerical Analysis and Scientific Computing; Theory and Algorithms
• Online Access: https://ink.library.smu.edu.sg/sis_research/3061; https://ink.library.smu.edu.sg/context/sis_research/article/4061/viewcontent/procamiasymp00001_1125.pdf
• Institution: Singapore Management University

With the huge amount of data collected by scientists in the molecular genetics community in recent years, there exists a need to develop some novel algorithms based on existing data mining techniques to discover useful information from genome databases. We propose an algorithm that integrates the statistical method, association rule mining, and classification rule mining in the discovery of allelic combinations of genes that are peculiar to certain phenotypes of diseased patients.