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Vector Seeds: An Extension to Spaced Seeds Allows Substantial Improvements in Sensitivity and Specificity

  • Broňa Brejová
  • Daniel G. Brown
  • Tomáš Vinař
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2812)

Abstract

We present improved techniques for finding homologous regions in DNA and protein sequences. Our approach focuses on the core region of a local pairwise alignment; we suggest new ways to characterize these regions that allow marked improvements in both specificity and sensitivity over existing techniques for sequence alignment. For any such characterization, which we call a vector seed, we give an efficient algorithm that estimates the specificity and sensitivity of that seed under reasonable probabilistic models of sequence. We also characterize the probability of a match when an alignment is required to have multiple hits before it is detected. Our extensions fit well with existing approaches to sequence alignment, while still offering substantial improvement in runtime and sensitivity, particularly for the important problem of identifying matches between homologous coding DNA sequences.

Keywords

False Positive Rate False Negative Rate Hash Table Protein Alignment Good Seed 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Broňa Brejová
    • 1
  • Daniel G. Brown
    • 1
  • Tomáš Vinař
    • 1
  1. 1.School of Computer ScienceUniversity of WaterlooWaterlooCanada

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