RNA Tree Comparisons via Unrooted Unordered Alignments

  • Nimrod Milo
  • Shay Zakov
  • Erez Katzenelson
  • Eitan Bachmat
  • Yefim Dinitz
  • Michal Ziv-Ukelson
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7534)


We generalize some current approaches for RNA tree alignment, which are traditionally confined to ordered rooted mappings, to also consider unordered unrooted mappings. We define the Homeomorphic Subtree Alignment problem, and present a new algorithm which applies to several modes, including global or local, ordered or unordered, and rooted or unrooted tree alignments. Our algorithm generalizes previous algorithms that either solved the problem in an asymmetric manner, or were restricted to the rooted and/or ordered cases. Focusing here on the most general unrooted unordered case, we show that our algorithm has an O(n T n S min (d T , d S )) time complexity, where n T and n S are the number of nodes and d T and d S are the maximum node degrees in the input trees T and S, respectively. This maintains (and slightly improves) the time complexity of previous, less general algorithms for the problem. Supplemental materials, source code, and web-interface for our tool are found in .


Input Tree Hammerhead Ribozyme Bipartite Match Tree Edit Distance Unordered Tree 
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 2012

Authors and Affiliations

  • Nimrod Milo
    • 1
  • Shay Zakov
    • 2
  • Erez Katzenelson
    • 1
  • Eitan Bachmat
    • 1
  • Yefim Dinitz
    • 1
  • Michal Ziv-Ukelson
    • 1
  1. 1.Dept. of Computer ScienceBen-Gurion University of the NegevIsrael
  2. 2.Dept. of Computer Science and EngineeringUC San DiegoLa JollaUSA

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