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What’s Behind Blast

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Models and Algorithms for Genome Evolution

Part of the book series: Computational Biology ((COBO,volume 19))

Abstract

The BLAST search engine was published and released in 1990. It is a heuristic that uses the idea of a neighborhood to find seed matches that are then extended. This approach came from work that this author was doing to lever these ideas to arrive at a deterministic algorithm with a characterized and superior time complexity. The resulting \(O(en^{\operatorname{pow}(e/p)} \log n)\) expected-time algorithm for finding all e-matches to a string of length p in a text of length n was completed in 1991. The function \(\operatorname{pow}( \epsilon )\) is 0 for ϵ=0 and concave increasing, so the algorithm is truly sublinear in that its running time is O(n c) for c<1 for ϵ sufficiently small. This paper reviews the history and the unfolding of the basic concepts, and it attempts to intuitively describe the deeper result whose time complexity, to this author’s knowledge, has yet to be improved upon.

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Author information

Authors and Affiliations

  1. MPI for Cellular Molecular Biology and Genetics, 01307, Dresden, Germany

    Gene Myers

Authors
  1. Gene Myers
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Correspondence to Gene Myers .

Editor information

Editors and Affiliations

  1. Department of Mathematics, Simon Fraser University, Burnaby, British Columbia, Canada

    Cedric Chauve

  2. Computer Science and Operations Research, University of Montreal, Montreal, Québec, Canada

    Nadia El-Mabrouk

  3. Biometry and Evolutionary Biology, INRIA Rhône-Alpes, University of Lyon, Villeurbanne, France

    Eric Tannier

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© 2013 Springer-Verlag London

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Myers, G. (2013). What’s Behind Blast. In: Chauve, C., El-Mabrouk, N., Tannier, E. (eds) Models and Algorithms for Genome Evolution. Computational Biology, vol 19. Springer, London. https://doi.org/10.1007/978-1-4471-5298-9_1

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  • DOI: https://doi.org/10.1007/978-1-4471-5298-9_1

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-4471-5297-2

  • Online ISBN: 978-1-4471-5298-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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