A Frequent Pattern Mining Method for Finding Planted Motifs of Unknown Length in DNA Sequences

DOI

10.2991/ijcis.2011.4.5.26How to use a DOI?

Keywords

Motif, frequent pattern, Apriori, downward closure property.

Abstract

Identification and characterization of gene regulatory binding motifs is one of the fundamental tasks toward systematically understanding the molecular mechanisms of transcriptional regulation. Recently, the problem has been abstracted as the challenge planted (l,d)-motif problem. Previous studies have developed numerous methods to solve the problem. But most of them need to specify the length l of a planted motif in advance and use depth first search strategy. In this study, we present an exact and efficient algorithm, called Apriori-Motif, without given the length l of a planted motif a priori. And a breadth first search strategy is used to prune search space quickly by the downward closure property utilized in Apriori, which is a classical algorithm for frequent pattern mining. Empirical study shows that Apriori-Motif is better than some existing methods.

Copyright

© 2011, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - JOUR
AU  - Caiyan Jia
AU  - Ruqian Lu
AU  - Lusheng Chen
PY  - 2011
DA  - 2011/09/01
TI  - A Frequent Pattern Mining Method for Finding Planted Motifs of Unknown Length in DNA Sequences
JO  - International Journal of Computational Intelligence Systems
SP  - 1032
EP  - 1041
VL  - 4
IS  - 5
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.2011.4.5.26
DO  - 10.2991/ijcis.2011.4.5.26
ID  - Jia2011
ER  -