Algorithms for approximate string matching
Information and Control
Efficient string matching with k mismatches
Theoretical Computer Science
Algorithms on strings, trees, and sequences: computer science and computational biology
Algorithms on strings, trees, and sequences: computer science and computational biology
An algorithm for finding novel gapped motifs in DNA sequences
RECOMB '98 Proceedings of the second annual international conference on Computational molecular biology
RECOMB '00 Proceedings of the fourth annual international conference on Computational molecular biology
Spelling Approximate Repeated or Common Motifs Using a Suffix Tree
LATIN '98 Proceedings of the Third Latin American Symposium on Theoretical Informatics
Theoretical and Empirical Comparisons of Approximate String Matching Algorithms
CPM '92 Proceedings of the Third Annual Symposium on Combinatorial Pattern Matching
Approximate String-Matching over Suffix Trees
CPM '93 Proceedings of the 4th Annual Symposium on Combinatorial Pattern Matching
Linear pattern matching algorithms
SWAT '73 Proceedings of the 14th Annual Symposium on Switching and Automata Theory (swat 1973)
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Gibbs sampling is a local search method that can be used to find novel motifs in a text string. In previous work [8], we have proposed a modified Gibbs sampler that can discover novel gapped motifs of varying lengths and occurrence rates in DNA or protein sequences. The Gibbs sampling method requires repeated searching of the text for the best match to a constantly evolving collection of aligned strings, and each search pass previously required θ(nl) time, where l is the length of the motif and n the length of the original sequence. This paper presents a novel method for using suffix trees to greatly improve the performance of the Gibbs sampling approach.