Algorithms for extracting
structured motifs using a suffix tree with an application to promoter
and regulatory site consensus identification
Laurent Marsan and Marie-France Sagot
Journal of Computational Biology, 7:345-360, 2000
The paper introduces two exact algorithms for extracting conserved
structured motifs from a set of DNA sequences. Structured motifs may
be described as an ordered collection of p >= 1 "boxes" (each
box corresponding to one part of the structured motif), p
substitution rates (one for each box) and p-1 intervals of
distance (one for each pair of successive boxes in the
collection). The contents of the boxes - that is, the motifs
themselves -- are unknown at the start of the algorithm. This is
precisely what the algorithms are meant to find. A suffix tree is used
for finding such motifs. The algorithms are efficient enough to be
able to infer site consensi, such as, for instance, promoter sequences
or regulatory sites, from a set of unaligned sequences corresponding
to the non coding regions upstream from all genes of a genome. In
particular, both algorithms time complexity scales linearly with
N^2 * n where n is the average length of the
sequences and N their number. An application to the
identification of promoter and regulatory consensus sequences in
bacterial genomes is shown.
key words: structured motif extraction, promoter and regulatory
site, consensus, model, suffix tree
Paper in postscript format
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