RNA multiple structural alignment with longest common subsequences
 Sergey Bereg,
 Marcin Kubica,
 Tomasz Waleń,
 Binhai Zhu
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In this paper, we present a new model for RNA multiple sequence structural alignment based on the longest common subsequence. We consider both the offline and online cases. For the offline 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 online 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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 Title
 RNA multiple structural alignment with longest common subsequences
 Journal

Journal of Combinatorial Optimization
Volume 13, Issue 2 , pp 179188
 Cover Date
 20070201
 DOI
 10.1007/s108780069020x
 Print ISSN
 13826905
 Online ISSN
 15732886
 Publisher
 Kluwer Academic PublishersPlenum Publishers
 Additional Links
 Topics
 Keywords

 RNA multiple structure alignment
 Longest common subsequence
 Dynamic programming
 Industry Sectors
 Authors

 Sergey Bereg ^{(1)}
 Marcin Kubica ^{(2)}
 Tomasz Waleń ^{(2)}
 Binhai Zhu ^{(3)}
 Author Affiliations

 1. Department of Computer Science, University of Texas at Dallas, Richardson, TX, 750830688, USA
 2. Institute of Informatics, Warsaw University, Banacha 2, 02097, Warszawa, Poland
 3. Department of Computer Science, Montana State University, Bozeman, MT, 597173880, USA