Efficient Mining of Interesting Patterns in Large Biological Sequences
Genomics & Informatics
;
: 44-50, 2012.
Artículo
en Inglés
| WPRIM
| ID: wpr-155515
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.
Texto completo:
Disponible
Índice:
WPRIM (Pacífico Occidental)
Asunto principal:
ADN
/
Secuencia de Bases
/
Biología Computacional
/
Minería
Idioma:
Inglés
Revista:
Genomics & Informatics
Año:
2012
Tipo del documento:
Artículo
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