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MUSA: a parameter free algorithm for the identification of biologically significant motifs
Author(s) -
Nuno D. Mendes,
Ana Casimiro,
Pedro M. Santos,
Isabel SáCorreia,
Arlindo L. Oliveira,
Ana T. Freitas
Publication year - 2006
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btl537
Subject(s) - motif (music) , computer science , algorithm , structural motif , biological data , artificial intelligence , computational biology , data mining , biology , bioinformatics , biochemistry , physics , acoustics
The ability to identify complex motifs, i.e. non-contiguous nucleotide sequences, is a key feature of modern motif finders. Addressing this problem is extremely important, not only because these motifs can accurately model biological phenomena but because its extraction is highly dependent upon the appropriate selection of numerous search parameters. Currently available combinatorial algorithms have proved to be highly efficient in exhaustively enumerating motifs (including complex motifs), which fulfill certain extraction criteria. However, one major problem with these methods is the large number of parameters that need to be specified.

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