%0 Journal Article
%T Efficient sampling of RNA secondary structures from the Boltzmann ensemble of low-energy: The boustrophedon method
%+ Algorithms and Models for Integrative Biology (AMIB )
%+ Laboratoire d'informatique de l'École polytechnique [Palaiseau] (LIX)
%A Ponty, Yann
%< avec comité de lecture
%@ 0303-6812
%J Journal of Mathematical Biology
%I Springer Verlag (Germany)
%V 56
%N 1-2
%P 107--127
%8 2008
%D 2008
%R 10.1007/s00285-007-0137-z
%Z Computer Science [cs]/Bioinformatics [q-bio.QM]
%Z Life Sciences [q-bio]/Quantitative Methods [q-bio.QM]Journal articles
%X We adapt here a surprising technique, the boustrophedon method, to speed up the sampling of RNA secondary structures from the Boltzmann low-energy ensemble. This technique is simple and its implementation straight-forward, as it only requires a permutation in the order of some operations already performed in the stochastic traceback stage of these algorithms. It nevertheless greatly improves their worst-case complexity from O(n^2) to O(n log(n)), for n the size of the original sequence. Moreover the average-case complexity of the generation is shown to be improved from O(n√n) to O(n log(n)) in an Boltzmann-weighted homopolymer model based on the Nussinov–Jacobson free-energy model. These results are extended to the more realistic Turner free-energy model through experiments performed on both structured (Drosophilia melanogaster mRNA 5S) and hybrid (Staphylococcus aureus RNAIII) RNA sequences, using a boustrophedon modified version of the popular software UnaFold. This improvement allows for the sampling of greater and more significant sets of structures in a given time.
%G English
%L inria-00548863
%U https://inria.hal.science/inria-00548863
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