Parsing nucleic acid pseudoknotted secondary structure: algorithm and applications
Parsing nucleic acid pseudoknotted secondary structure: algorithm and applications
Accurate prediction of pseudoknotted nucleic acid secondary structure is an important computational challenge. Prediction algorithms based on dynamic programming aim to find a structure with minimum free energy according to some thermodynamic ("sum of loop energies") model that is implicit in the recurrences of the algorithm. However, a clear definition of what exactly are the loops in pseudoknotted structures, and their associated energies, has been lacking. In this work, we present a complete classification of loops in pseudoknotted nucleic secondary structures, and describe the Rivas and Eddy and other energy models as sum-of-loops energy models. We give a linear time algorithm for parsing a pseudoknotted secondary structure into its component loops. We give two applications of our parsing algorithm. The first is a linear time algorithm to calculate the free energy of a pseudoknotted secondary structure. This is useful for heuristic prediction algorithms, which are widely used since (pseudoknotted) RNA secondary structure prediction is NP-hard. The second application is a linear time algorithm to test the generality of the dynamic programming algorithm of Akutsu for secondary structure prediction.Together with previous work, we use this algorithm to compare the generality of state-of-the-art algorithms on real biological structures.
16-32
Rastegari, Baharak
6ba9e93c-53ba-4090-8f77-c1cb1568d7d1
Condon, Anne
a1c1e645-b4b0-4449-a18e-6e43a440cce8
24 March 2007
Rastegari, Baharak
6ba9e93c-53ba-4090-8f77-c1cb1568d7d1
Condon, Anne
a1c1e645-b4b0-4449-a18e-6e43a440cce8
Rastegari, Baharak and Condon, Anne
(2007)
Parsing nucleic acid pseudoknotted secondary structure: algorithm and applications.
Journal of Computational Biology, 14 (1), .
(doi:10.1089/cmb.2006.0108).
Abstract
Accurate prediction of pseudoknotted nucleic acid secondary structure is an important computational challenge. Prediction algorithms based on dynamic programming aim to find a structure with minimum free energy according to some thermodynamic ("sum of loop energies") model that is implicit in the recurrences of the algorithm. However, a clear definition of what exactly are the loops in pseudoknotted structures, and their associated energies, has been lacking. In this work, we present a complete classification of loops in pseudoknotted nucleic secondary structures, and describe the Rivas and Eddy and other energy models as sum-of-loops energy models. We give a linear time algorithm for parsing a pseudoknotted secondary structure into its component loops. We give two applications of our parsing algorithm. The first is a linear time algorithm to calculate the free energy of a pseudoknotted secondary structure. This is useful for heuristic prediction algorithms, which are widely used since (pseudoknotted) RNA secondary structure prediction is NP-hard. The second application is a linear time algorithm to test the generality of the dynamic programming algorithm of Akutsu for secondary structure prediction.Together with previous work, we use this algorithm to compare the generality of state-of-the-art algorithms on real biological structures.
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Published date: 24 March 2007
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Local EPrints ID: 426395
URI: http://eprints.soton.ac.uk/id/eprint/426395
ISSN: 1066-5277
PURE UUID: a98a2add-93a8-4599-a741-1a4806b6a55b
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Date deposited: 27 Nov 2018 17:30
Last modified: 16 Mar 2024 04:39
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Author:
Baharak Rastegari
Author:
Anne Condon
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