Genomics & Informatics

Korea Genome Organization (한국유전체학회)
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Efficient Mining of Interesting Patterns in Large Biological Sequences

  • Rashid, Md. Mamunur (Department of Computer Engineering, College of Electronics and Information, Kyung Hee University) ;
  • Karim, Md. Rezaul (Department of Computer Engineering, College of Electronics and Information, Kyung Hee University) ;
  • Jeong, Byeong-Soo (Department of Computer Engineering, College of Electronics and Information, Kyung Hee University) ;
  • Choi, Ho-Jin (Department of Computer Science, Korea Advanced Institute of Science and Technology)
  • Received : 2012.01.27
  • Accepted : 2012.02.10
  • Published : 2012.03.31
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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.

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References

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