title: An efficient approach to mining maximal contiguous frequent patterns from large DNA sequence databases.
abstract: Mining interesting patterns from DNA sequences is one of the most challenging tasks in bioinformatics and computational biology. Maximal contiguous frequent patterns are preferable for expressing the function and structure of DNA sequences and hence can capture the common data characteristics among related sequences. Biologists are interested in finding frequent orderly arrangements of motifs that are responsible for similar expression of a group of genes. In order to reduce mining time and complexity, however, most existing sequence mining algorithms either focus on finding short DNA sequences or require explicit specification of sequence lengths in advance. The challenge is to find longer sequences without specifying sequence lengths in advance. In this paper, we propose an efficient approach to mining maximal contiguous frequent patterns from large DNA sequence datasets. The experimental results show that our proposed approach is memory-efficient and mines maximal contiguous frequent patterns within a reasonable time.
authors.affiliation: Department of Computer Engineering, College of Electronics and Information, Kyung Hee University, Yongin 446-701, Korea.
authors.forename: Md Rezaul
authors.initials: MR
authors.lastname: Karim
authors.forename: Md Mamunur
authors.initials: MM
authors.lastname: Rashid
authors.forename: Byeong-Soo
authors.initials: BS
authors.lastname: Jeong
authors.forename: Ho-Jin
authors.initials: HJ
authors.lastname: Choi
keywords: DNA sequence; maximal contiguous frequent pattern; pattern mining; suffix tree