@InProceedings{SiebertBackofen:dist_meas:2005,
  author = 	 {Sven Siebert and Rolf Backofen},
  title = 	 {A new distance measure of RNA ensembles and its application to phylogenetic tree construction},
  booktitle = 	 {IEEE 2005 Symposium on Computational Intelligence in Bioinformatics and Computational Biology},
  pages = 	 {150-157},
  year = 	 {2005},
  editor = 	 {Gary B. Fogel},
  address = 	 {La Jolla, CA, USA},
  month = 	 {November},
  organization = {IEEE},
  abstract =     {A major challenge in RNA structure analysis is to 
                  infer common catalytic or regulatory functions based
                  on primary sequences and secondary structures. Some
                  programs have been developed that compare RNAs with
                  such given structures. Nevertheless, the most
                  important problem is that it is hard to determine
                  the adopted structures of RNAs which are a necessary
                  prerequisite to numerous applications; once a
                  structure has been assigned to a sequence (e.g. the
                  minimum free energy structure), it influences the
                  output of the programs and thus affects the
                  scientific result, especially when dealing with a
                  set of multiple RNAs. In this paper, we go one step
                  further and analyze distances between RNA structure
                  ensembles. They reflect structural relationships
                  computed basically on base-pairing probability
                  matrices.  We propose a distance measure between two
                  base-pairing probability matrices showing similar or
                  non-similar structural folding behaviour. This
                  includes the detection of shared optimal, suboptimal
                  and local secondary structures. Consequently, our
                  distance measure avoids falling into the trap of
                  fixing specific structures. A pairwise comparison
                  strategy in a set of multiple RNAs leads us to
                  construct a network of structural relationships
                  using the neighbour joining method.  Attempts to
                  predict phylogenetic trees are discussed and
                  demonstrated by means of viral RNAs.}, 
  user =         {siebert} 
}