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Linear time algorithm for parsing RNA secondary structure

Linear time algorithm for parsing RNA secondary structure
Linear time algorithm for parsing RNA secondary structure
Accurate prediction of pseudoknotted RNA secondary structure is an important computational challenge. Typical prediction algorithms 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 and stems in pseudoknotted structures, and their associated energies, has been lacking.

We present a comprehensive classification of loops in pseudoknotted RNA secondary structures. Building on an algorithm of Bader et al. we obtain a linear time algorithm for parsing a secondary structures into its component loops.

We also give 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. Finally, we give a linear time algorithm to test whether a secondary structure is in the class handled by Akutsu’s algorithm. Using our tests, we analyze the generality of Akutsu’s algorithm for real biological structures.
0302-9743
341-352
Springer
Rastegari, Baharak
6ba9e93c-53ba-4090-8f77-c1cb1568d7d1
Condon, Anne
a1c1e645-b4b0-4449-a18e-6e43a440cce8
Casadio, R.
Myers, G.
Rastegari, Baharak
6ba9e93c-53ba-4090-8f77-c1cb1568d7d1
Condon, Anne
a1c1e645-b4b0-4449-a18e-6e43a440cce8
Casadio, R.
Myers, G.

Rastegari, Baharak and Condon, Anne (2005) Linear time algorithm for parsing RNA secondary structure. In, Casadio, R. and Myers, G. (eds.) Algorithms in Bioinformatics. WABI 2005. (Lecture Notes in Computer Science: Algorithms in Bioinformatics, 3692) Berlin; Heidelberg. Springer, pp. 341-352. (doi:10.1007/11557067_28).

Record type: Book Section

Abstract

Accurate prediction of pseudoknotted RNA secondary structure is an important computational challenge. Typical prediction algorithms 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 and stems in pseudoknotted structures, and their associated energies, has been lacking.

We present a comprehensive classification of loops in pseudoknotted RNA secondary structures. Building on an algorithm of Bader et al. we obtain a linear time algorithm for parsing a secondary structures into its component loops.

We also give 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. Finally, we give a linear time algorithm to test whether a secondary structure is in the class handled by Akutsu’s algorithm. Using our tests, we analyze the generality of Akutsu’s algorithm for real biological structures.

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Published date: 2005

Identifiers

Local EPrints ID: 426394
URI: http://eprints.soton.ac.uk/id/eprint/426394
ISSN: 0302-9743
PURE UUID: e9709ecd-abec-4b2c-8e7d-900008e2a756
ORCID for Baharak Rastegari: ORCID iD orcid.org/0000-0002-0985-573X

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Date deposited: 27 Nov 2018 17:30
Last modified: 10 Nov 2021 03:56

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Contributors

Author: Baharak Rastegari ORCID iD
Author: Anne Condon
Editor: R. Casadio
Editor: G. Myers

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