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Multiple filtration and approximate pattern matching

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Abstract

Given a text of lengthn and a query of lengthq, we present an algorithm for finding all locations ofm-tuples in the text and in the query that differ by at mostk mismatches. This problem is motivated by the dot-matrix constructions for sequence comparison and optimal oligonucleotide probe selection routinely used in molecular biology. In the caseq=m the problem coincides with the classicalapproximate string matching with k mismatches problem. We present a new approach to this problem based on multiple hashing, which may have advantages over some sophisticated and theoretically efficient methods that have been proposed. This paper describes a two-stage process. The first stage (multiple filtration) uses a new technique to preselect roughly similarm-tuples. The second stage compares thesem-tuples using an accurate method. We demonstrate the advantages of multiple filtration in comparison with other techniques for approximate pattern matching.

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Authors and Affiliations

  1. Department of Mathematics, University of Southern California, 90084-1113, Los Angeles, CA, USA

    P. A. Pevzner & M. S. Waterman

  2. Computer Science Department, The Pennsylvania State University, 16802, University Park, PA, USA

    P. A. Pevzner

  3. Department of Molecular Biology, University of Southern California, 90089-1113, Los Angeles, CA, USA

    M. S. Waterman

Authors
  1. P. A. Pevzner
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  2. M. S. Waterman
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Additional information

Communicated by E. W. Myers.

This research was supported in part by the National Science Foundation under Grant No. DMS 90-05833 and the National Institute of Health under Grant No. GM-36230.

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Pevzner, P.A., Waterman, M.S. Multiple filtration and approximate pattern matching. Algorithmica 13, 135–154 (1995). https://doi.org/10.1007/BF01188584

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  • DOI: https://doi.org/10.1007/BF01188584

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