Document Detail

Efficient mining of interesting patterns in large biological sequences.
MedLine Citation:
PMID:  23105928     Owner:  NLM     Status:  PubMed-not-MEDLINE    
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.
Md Mamunur Rashid; Md Rezaul Karim; Byeong-Soo Jeong; Ho-Jin Choi
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Publication Detail:
Type:  Journal Article     Date:  2012-03-31
Journal Detail:
Title:  Genomics & informatics     Volume:  10     ISSN:  2234-0742     ISO Abbreviation:  Genomics Inform     Publication Date:  2012 Mar 
Date Detail:
Created Date:  2012-10-29     Completed Date:  2012-10-30     Revised Date:  2013-05-30    
Medline Journal Info:
Nlm Unique ID:  101223836     Medline TA:  Genomics Inform     Country:  Korea (South)    
Other Details:
Languages:  eng     Pagination:  44-50     Citation Subset:  -    
Department of Computer Engineering, College of Electronics and Information, Kyung Hee University, Yongin 446-701, Korea.
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