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RNA multiple structural alignment with longest common subsequences

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Abstract

In this paper, we present a new model for RNA multiple sequence structural alignment based on the longest common subsequence. We consider both the off-line and on-line cases. For the off-line case, i.e., when the longest common subsequence is given as a linear graph with n vertices, we first present a polynomial O(n 2) time algorithm to compute its maximum nested loop. We then consider a slightly different problem—the Maximum Loop Chain problem and present an algorithm which runs in O(n 5) time. For the on-line case, i.e., given m RNA sequences of lengths n, compute the longest common subsequence of them such that this subsequence either induces a maximum nested loop or the maximum number of matches, we present efficient algorithms using dynamic programming when m is small.

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Authors and Affiliations

  1. Department of Computer Science, University of Texas at Dallas, Richardson, TX, 75083-0688, USA

    Sergey Bereg

  2. Institute of Informatics, Warsaw University, Banacha 2, 02-097, Warszawa, Poland

    Marcin Kubica & Tomasz Waleń

  3. Department of Computer Science, Montana State University, Bozeman, MT, 59717-3880, USA

    Binhai Zhu

Authors
  1. Sergey Bereg
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  2. Marcin Kubica
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  3. Tomasz Waleń
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  4. Binhai Zhu
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Corresponding author

Correspondence to Binhai Zhu.

Additional information

This research is partially supported by EPSCOR Visiting Scholar's Program and MSU Short-term Professional Development Program.

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Bereg, S., Kubica, M., Waleń, T. et al. RNA multiple structural alignment with longest common subsequences. J Comb Optim 13, 179–188 (2007). https://doi.org/10.1007/s10878-006-9020-x

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  • DOI: https://doi.org/10.1007/s10878-006-9020-x

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