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MotifCut: regulatory motifs finding with maximum density subgraphs
Author(s) -
Eugene Fratkin,
Brian Naughton,
Douglas L. Brutlag,
Serafim Batzoglou
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/btl243
Subject(s) - pairwise comparison , motif (music) , computer science , theoretical computer science , combinatorics , algorithm , mathematics , artificial intelligence , physics , acoustics
DNA motif finding is one of the core problems in computational biology, for which several probabilistic and discrete approaches have been developed. Most existing methods formulate motif finding as an intractable optimization problem and rely either on expectation maximization (EM) or on local heuristic searches. Another challenge is the choice of motif model: simpler models such as the position-specific scoring matrix (PSSM) impose biologically unrealistic assumptions such as independence of the motif positions, while more involved models are harder to parametrize and learn.

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