Efficient Mining of Interesting Patterns in Large Biological Sequences

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,...
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Autor*in:	Md. Mamunur Rashid [verfasserIn] Md. Rezaul Karim [verfasserIn] Byeong-Soo Jeong [verfasserIn] Ho-Jin Choi [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2012

Schlagwörter:	DNA sequence index-based method information gain pattern mining

Übergeordnetes Werk:	In: Genomics & Informatics - Korea Genome Organization, 2017, 10(2012), 1, Seite 44-50
Übergeordnetes Werk:	volume:10 ; year:2012 ; number:1 ; pages:44-50

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc Journal toc

DOI / URN:	10.5808/GI.2012.10.1.44

Katalog-ID:	DOAJ021308454

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source	In Genomics & Informatics 10(2012), 1, Seite 44-50 volume:10 year:2012 number:1 pages:44-50
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topic_facet	DNA sequence index-based method information gain pattern mining Genetics
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authorswithroles_txt_mv	Md. Mamunur Rashid @@aut@@ Md. Rezaul Karim @@aut@@ Byeong-Soo Jeong @@aut@@ Ho-Jin Choi @@aut@@
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author	Md. Mamunur Rashid
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topic_title	QH426-470 Efficient Mining of Interesting Patterns in Large Biological Sequences DNA sequence index-based method information gain pattern mining
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title_sort	efficient mining of interesting patterns in large biological sequences
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title_auth	Efficient Mining of Interesting Patterns in Large Biological Sequences
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.
abstractGer	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.
abstract_unstemmed	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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title_short	Efficient Mining of Interesting Patterns in Large Biological Sequences
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Efficient Mining of Interesting Patterns in Large Biological Sequences

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