MADMX: A Novel Strategy for Maximal Dense Motif Extraction - Computer Science > Data Structures and AlgorithmsReportar como inadecuado




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Abstract: We develop, analyze and experiment with a new tool, called MADMX, whichextracts frequent motifs, possibly including don-t care characters, frombiological sequences. We introduce density, a simple and flexible measure forbounding the number of don-t cares in a motif, defined as the ratio of solidi.e., different from don-t care characters to the total length of the motif.By extracting only maximal dense motifs, MADMX reduces the output size andimproves performance, while enhancing the quality of the discoveries. Theefficiency of our approach relies on a newly defined combining operation,dubbed fusion, which allows for the construction of maximal dense motifs in abottom-up fashion, while avoiding the generation of nonmaximal ones. We provideexperimental evidence of the efficiency and the quality of the motifs returnedby MADMX



Autor: Roberto Grossi, Andrea Pietracaprina, Nadia Pisanti, Geppino Pucci, Eli Upfal, Fabio Vandin

Fuente: https://arxiv.org/







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