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A Framework for Space-Efficient String Kernels

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Combinatorial Pattern Matching (CPM 2015)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9133))

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Abstract

String kernels are typically used to compare genome-scale sequences whose length makes alignment impractical, yet their computation is based on data structures that are either space-inefficient, or incur large slowdowns. We show that a number of exact string kernels, like the \(k\)-mer kernel, the substrings kernels, a number of length-weighted kernels, the minimal absent words kernel, and kernels with Markovian corrections, can all be computed in \(O(nd)\) time and in \(o(n)\) bits of space in addition to the input, using just a \(\mathtt {rangeDistinct}\) data structure on the Burrows-Wheeler transform of the input strings that takes \(O(d)\) time per element in its output. The same bounds hold for a number of measures of compositional complexity based on multiple values of \(k\), like the \(k\)-mer profile and the \(k\)-th order empirical entropy, and for calibrating the value of \(k\) using the data.

This work was partially supported by Academy of Finland under grant 284598 (Center of Excellence in Cancer Genetics Research).

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Authors and Affiliations

  1. Department of Computer Science, University of Helsinki, Helsinki, Finland

    Djamal Belazzougui & Fabio Cunial

  2. Helsinki Institute for Information Technology, Helsinki, Finland

    Djamal Belazzougui & Fabio Cunial

Authors
  1. Djamal Belazzougui
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  2. Fabio Cunial
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Corresponding author

Correspondence to Fabio Cunial .

Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Verona, Verona, Italy

    Ferdinando Cicalese

  2. Department of Computer Science, Bar-Ilan University, Ramat Gan, Israel

    Ely Porat

  3. Department of Computer Science, University of Salerno, Fisciano, Italy

    Ugo Vaccaro

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Belazzougui, D., Cunial, F. (2015). A Framework for Space-Efficient String Kernels. In: Cicalese, F., Porat, E., Vaccaro, U. (eds) Combinatorial Pattern Matching. CPM 2015. Lecture Notes in Computer Science(), vol 9133. Springer, Cham. https://doi.org/10.1007/978-3-319-19929-0_2

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  • DOI: https://doi.org/10.1007/978-3-319-19929-0_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-19928-3

  • Online ISBN: 978-3-319-19929-0

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