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  1. Home > Articles & Issues >
  2. Articles >
  3. Counting RNA pseudok ...
Conference paper

Counting RNA pseudoknotted structures (extended abstract)

Cédric Saule (1) (2) (3), Mireille Regnier (4) (5), Jean-Marc Steyaert (5) (4), Alain Denise ORCID (1) (6) (4)
(1) Laboratoire de Recherche en Informatique
(2) Inria Saclay - Ile de France
(3) Centre Inria de Saclay
(4) Algorithms and Models for Integrative Biology
(5) Laboratoire d'informatique de l'École polytechnique [Palaiseau]
(6) Institut de génétique et microbiologie [Orsay]
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Imported on
January 31, 2017
Published on
December 31, 2009
Last modified on
March 31, 2025
Volume
DMTCS Proceedings vol. AN, 22nd International Conference on Formal Power Series and Algebraic Combinatorics (FPSAC 2010)
Proceedings
DOI
10.46298/dmtcs.2834
License
https://about.hal.science/hal-authorisation-v1
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Counting RNA pseudoknotted structures (extended abstract)

Cédric Saule (1) (2) (3), Mireille Regnier (4) (5), Jean-Marc Steyaert (5) (4), Alain Denise ORCID (1) (6) (4)
(1) Laboratoire de Recherche en Informatique
(2) Inria Saclay - Ile de France
(3) Centre Inria de Saclay
(4) Algorithms and Models for Integrative Biology
(5) Laboratoire d'informatique de l'École polytechnique [Palaiseau]
(6) Institut de génétique et microbiologie [Orsay]
Abstract
English
In 2004, Condon and coauthors gave a hierarchical classification of exact RNA structure prediction algorithms according to the generality of structure classes that they handle. We complete this classification by adding two recent prediction algorithms. More importantly, we precisely quantify the hierarchy by giving closed or asymptotic formulas for the theoretical number of structures of given size n in all the classes but one. This allows to assess the tradeoff between the expressiveness and the computational complexity of RNA structure prediction algorithms. \par
French
En 2004, Condon et ses coauteurs ont défini une classification des algorithmes exacts de prédiction de structure d'ARN, selon le degré de généralité des classes de structures qu'ils sont capables de prédire. Nous complétons cette classification en y ajoutant deux algorithmes récents. Chose plus importante, nous quantifions la hiérarchie des algorithmes, en donnant des formules closes ou asymptotiques pour le nombre théorique de structures de taille donnée n dans chacune des classes, sauf une. Ceci fournit un moyen d'évaluer, pour chaque algorithme, le compromis entre son degré de généralité et sa complexité.
Keywords
  • [MATH.MATH-CO]Mathematics [math]/Combinatorics [math.CO]
  • [INFO.INFO-DM]Computer Science [cs]/Discrete Mathematics [cs.DM]
  • bioinformatics
  • RNA structures
  • pseudoknots
  • enumeration
  • bijective combinatorics
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