Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Bases of Motifs for Generating Repeated Patterns with Wild Cards
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Incremental discovery of the irredundant motif bases for all suffixes of a string in O(n2logn) time
Theoretical Computer Science
Pattern Discovery in Bioinformatics: Theory & Algorithms
Pattern Discovery in Bioinformatics: Theory & Algorithms
Mining maximal flexible patterns in a sequence
JSAI'07 Proceedings of the 2007 conference on New frontiers in artificial intelligence
VARUN: Discovering Extensible Motifs under Saturation Constraints
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Structural analysis of gapped motifs of a string
MFCS'07 Proceedings of the 32nd international conference on Mathematical Foundations of Computer Science
Optimal offline extraction of irredundant motif bases
COCOON'07 Proceedings of the 13th annual international conference on Computing and Combinatorics
Note: Extracting string motif bases for quorum higher than two
Theoretical Computer Science
Parallel motif extraction from very long sequences
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
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We develop, analyze and experiment with a new tool, called madmx, which extracts frequent motifs, possibly including don't care characters, from biological sequences. We introduce density, a simple and flexible measure for bounding the number of don't cares in a motif, defined as the ratio of solid (i.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 and improves performance, while enhancing the quality of the discoveries. The efficiency of our approach relies on a newly defined combining operation, dubbed fusion, which allows for the construction of maximal dense motifs in a bottom-up fashion, while avoiding the generation of nonmaximal ones. We provide experimental evidence of the efficiency and the quality of the motifs returned by MADMX.