title: Efficient mining of interesting patterns in large biological sequences.
abstract: Pattern discovery in biological sequences (e.g., DNA sequences) is one of the most challenging tasks in computational biology and bioinformatics. So far, in most approaches, the number of occurrences is a major measure of determining whether a pattern is interesting or not. In computational biology, however, a pattern that is not frequent may still be considered very informative if its actual support frequency exceeds the prior expectation by a large margin. In this paper, we propose a new interesting measure that can provide meaningful biological information. We also propose an efficient index-based method for mining such interesting patterns. Experimental results show that our approach can find interesting patterns within an acceptable computation time.
authors.affiliation: Department of Computer Engineering, College of Electronics and Information, Kyung Hee University, Yongin 446-701, Korea.
authors.forename: Md Mamunur
authors.initials: MM
authors.lastname: Rashid
authors.forename: Md Rezaul
authors.initials: MR
authors.lastname: Karim
authors.forename: Byeong-Soo
authors.initials: BS
authors.lastname: Jeong
authors.forename: Ho-Jin
authors.initials: HJ
authors.lastname: Choi
keywords: DNA sequence; index-based method; information gain; pattern mining