Approximate string-matching with q-grams and maximal matches
Theoretical Computer Science - Selected papers of the Combinatorial Pattern Matching School
Text algorithms
A fast string searching algorithm
Communications of the ACM
Efficient string matching: an aid to bibliographic search
Communications of the ACM
Flexible pattern matching in strings: practical on-line search algorithms for texts and biological sequences
Accelerating Protein Classification Using Suffix Trees
Proceedings of the Eighth International Conference on Intelligent Systems for Molecular Biology
Shift-or string matching with super-alphabets
Information Processing Letters
Bioinformatics
Fast search algorithms for position specific scoring matrices
BIRD'07 Proceedings of the 1st international conference on Bioinformatics research and development
Algorithms for weighted matching
SPIRE'07 Proceedings of the 14th international conference on String processing and information retrieval
Large scale matching for position weight matrices
CPM'06 Proceedings of the 17th Annual conference on Combinatorial Pattern Matching
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Position weight matrices are an important method for modeling signals or motifs in biological sequences, both in DNA and protein contexts. In this paper, we present fast algorithms for the problem of finding significant matches of such matrices. Our algorithms are of the online type, and they generalize classical multipattern matching, filtering, and superalphabet techniques of combinatorial string matching to the problem of weight matrix matching. Several variants of the algorithms are developed, including multiple matrix extensions that perform the search for several matrices in one scan through the sequence database. Experimental performance evaluation is provided to compare the new techniques against each other as well as against some other online and index-based algorithms proposed in the literature. Compared to the brute-force O(mn) approach, our solutions can be faster by a factor that is proportional to the matrix length m. Our multiple-matrix filtration algorithm had the best performance in the experiments. On a current PC, this algorithm finds significant matches (p = 0.0001) of the 123 JASPAR matrices in the human genome in about 18 minutes.