Abstract
This paper describes a general method for controlling the running time of similarity search algorithms. Our method can be used in conjunction with the seed-and-extend paradigm employed by many search algorithms, including BLAST. We introduce the concept of a seed tree, and provide a seed tree-pruning algorithm that affects the specificity in a predictable manner. The algorithm uses a single parameter to control the speed of the similarity search. The parameter enables us to reach arbitrary levels between the exponential increases in running time that are typical of seed-and-extend methods.
Research supported by NSERC grant 250391-02.
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Csűrös, M. (2004). Performing Local Similarity Searches with Variable Length Seeds. In: Sahinalp, S.C., Muthukrishnan, S., Dogrusoz, U. (eds) Combinatorial Pattern Matching. CPM 2004. Lecture Notes in Computer Science, vol 3109. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-27801-6_28
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DOI: https://doi.org/10.1007/978-3-540-27801-6_28
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