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In the structured motif extraction problem, the component motifs M i are unknown before the extraction.
We first introduce our basic approach for common structured motif extraction problem.
The 2-stage approach is also used by Ex Motif[ 26] to solve the frequent structured motif extraction problem.
We compare our results with the latest version of RISO [ 15- 17] (called RISOTTO [ 17]), the best previous algorithm for structured motif extraction problem.
The challenges for motif extraction problem are two-fold: one is to design an efficient algorithm to enumerate the frequent motifs; the other is to statistically validate the extracted motifs and report the significant ones.
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In this paper, we propose EXMOTIF, an efficient algorithm for both the structured motif extraction problems.
Structured motif extraction problems, in which variable number of gaps are allowed, have attracted much attention recently, where the structured motifs can be extracted either from multiple sequences [ 14- 21] or from a single sequence [ 22, 23].
We use CPs extracted by MEX (Motif Extraction algorithm) to study evolutionary processes in olfactory receptors.
We extract deterministic motifs from ORs belonging to ten species using the MEX (Motif Extraction) algorithm, thus defining Common Peptides (CPs) characteristic to ORs.
In ExMotif: Efficient Structured Motif Extraction, Yongqiang Zhang and Mohammed J. Zaki [ 3], describe a new algorithm called EXMOTIF to extract frequent motifs from DNA sequences.
The extrapolated rank estimation for motif extraction was 1,286.
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