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Constraint-Based Strategy for Pairwise RNA Secondary Structure Prediction

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Book cover Progress in Artificial Intelligence (EPIA 2009)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5816))

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Abstract

RNA secondary structure prediction depends on context. When only a few (sometimes putative) RNA homologs are available, one of the most famous approach is based on a set of recursions proposed by Sankoff in 1985. Although this modus operandi insures an algorithmically optimal result, the main drawback lies in its prohibitive time and space complexities. A series of heuristics were developed to face that difficulty and turn the recursions usable. In front of the inescapable intricacy of the question when handling the full thermodynamic model, we come back in the present paper to a biologically simplified model that helps focusing on the algorithmic issues we want to overcome. We expose our ongoing developments by using the constraints framework which we believe is a powerful paradigm for heuristic design. We give evidence that the main heuristics proposed by others (structural and alignment banding, multi-loop restriction) can be refined in order to produce a substantial gain both in time computation and space requirements. A beta implementation of our approach, that we named ARNICA, exemplify that gain on a sample set that remains unaffordable to other methods. The sources and sample tests of ARNICA are available at http://centria.di.fct.unl.pt/~op/arnica.tar.gz

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Authors and Affiliations

  1. CENTRIA - Centre for Artificial Intelligence - Dep. de Informática, FCT/UNL, Quinta da Torre, 2829-516, CAPARICA, Portugal

    Olivier Perriquet & Pedro Barahona

Authors
  1. Olivier Perriquet
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  2. Pedro Barahona
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Editor information

Editors and Affiliations

  1. IEETA/Department of Electronics & Telecommunication, University of Aveiro, Campus Santiago, P.O. Box, 3810-153, Aveiro, Portugal

    Luís Seabra Lopes

  2. LSE-IEETA/DETI, Universidade de Aveiro, Portugal

    Nuno Lau

  3. Universidade de Aveiro, Aveiro, Portugal

    Pedro Mariano

  4. School of Informatics, Indiana University, Bloomington, IN, USA, and Computational Biology Collaboratorium, Instituto ulbenkian da Ciencia, Portugal

    Luís M. Rocha

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© 2009 Springer-Verlag Berlin Heidelberg

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Perriquet, O., Barahona, P. (2009). Constraint-Based Strategy for Pairwise RNA Secondary Structure Prediction. In: Lopes, L.S., Lau, N., Mariano, P., Rocha, L.M. (eds) Progress in Artificial Intelligence. EPIA 2009. Lecture Notes in Computer Science(), vol 5816. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04686-5_8

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  • DOI: https://doi.org/10.1007/978-3-642-04686-5_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-04685-8

  • Online ISBN: 978-3-642-04686-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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