Genomics Inform.  2012 Mar;10(1):51-57. 10.5808/GI.2012.10.1.51.

An Efficient Approach to Mining Maximal Contiguous Frequent Patterns from Large DNA Sequence Databases

• Karim MR
• Rashid MM
• Jeong BS
• Choi HJ

• KMID: 2053285
• DOI: http://doi.org/10.5808/GI.2012.10.1.51

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.

Keyword

DNA sequence; maximal contiguous frequent pattern; pattern mining; suffix tree

MeSH Terms

Base Sequence
Computational Biology
Databases, Nucleic Acid
DNA
Mining
DNA