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Efficient mining of interesting patterns in large biological sequences.
MedLine Citation:
PMID:  23105928     Owner:  NLM     Status:  PubMed-not-MEDLINE    
Abstract/OtherAbstract:
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:
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:  -    
Affiliation:
Department of Computer Engineering, College of Electronics and Information, Kyung Hee University, Yongin 446-701, Korea.
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