DIMACS TR: 2009-15
Efficient discovery of common patterns in sequences over large alphabets
Authors: Pavel Kuksa and Vladimir Pavlovic
We consider the problem of identifying motifs, recurring or conserved patterns, in the data modeled as strings or sequences. In particular, we present a new deterministic algorithm for finding patterns that are embedded as exact or inexact instances in all or most of the input strings. The proposed algorithm (1) improves search efficiency compared to existing algorithms, and (2) scales well with the size of alphabet. Our algorithm is several orders of magnitude faster than existing deterministic algorithms for common pattern identification. We evaluate our algorithm on benchmark motif finding problems and real applications in biological sequence analysis and show that our algorithm maintains predictive performance with significant running time improvements.
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