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    Fast algorithms for approximate circular string matching

    Access Status
    Open access via publisher
    Authors
    Barton, C.
    Iliopoulos, Costas
    Pissis, S.
    Date
    2014
    Type
    Journal Article
    
    Metadata
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    Citation
    Barton, C. and Iliopoulos, C. and Pissis, S. 2014. Fast algorithms for approximate circular string matching. Algorithms for Molecular Biology. 9 (1).
    Source Title
    Algorithms for Molecular Biology
    DOI
    10.1186/1748-7188-9-9
    ISSN
    1748-7188
    School
    Department of Mathematics and Statistics
    URI
    http://hdl.handle.net/20.500.11937/21124
    Collection
    • Curtin Research Publications
    Abstract

    Background: Circular string matching is a problem which naturally arises in many biological contexts. It consists in finding all occurrences of the rotations of a pattern of length m in a text of length n. There exist optimal average-case algorithms for exact circular string matching. Approximate circular string matching is a rather undeveloped area.Results: In this article, we present a suboptimal average-case algorithm for exact circular string matching requiring time O(n). Based on our solution for the exact case, we present two fast average-case algorithms for approximate circular string matching with k-mismatches, under the Hamming distance model, requiring time O(n) for moderate values of k, that is k = O(m/ logm). We show how the same results can be easily obtained under the edit distancemodel. The presented algorithms are also implemented as library functions. Experimental results demonstrate thatthe functions provided in this library accelerate the computations by more than three orders of magnitude compared to a naïve approach.Conclusions: We present two fast average-case algorithms for approximate circular string matching with k-mismatches; and show that they also perform very well in practice. The importance of our contribution is underlined by the fact that the provided functions may be seamlessly integrated into any biological pipeline. The source code of the library is freely available at http://www.inf.kcl.ac.uk/research/projects/asmf/.

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