Classifying RNA pseudoknotted structures
Classifying RNA pseudoknotted structures
Computational prediction of the minimum free energy (mfe) secondary structure of an RNA molecule from its base sequence is valuable in understanding the structure and function of the molecule. Since the general problem of predicting pseudoknotted secondary structures is NP-hard, several algorithms have been proposed that find the mfe secondary structure from a restricted class of secondary structures. In this work, we order the algorithms by generality of the structure classes that they handle. We provide simple characterizations of the classes of structures handled by four algorithms, as well as linear time methods to test whether a given secondary structure is in three of these classes. We report on the percentage of biological structures from the PseudoBase and Gutell databases that are handled by these three algorithms.
35-50
Condon, Anne
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Davy, Beth
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Rastegari, Baharak
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Zhao, Shelly
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Tarrant, Finbarr
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12 June 2004
Condon, Anne
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Davy, Beth
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Rastegari, Baharak
6ba9e93c-53ba-4090-8f77-c1cb1568d7d1
Zhao, Shelly
5f8e874d-4b77-49e0-a35f-77b168d8e27f
Tarrant, Finbarr
9d4dc897-c6df-4863-82dd-e676092758ad
Condon, Anne, Davy, Beth, Rastegari, Baharak, Zhao, Shelly and Tarrant, Finbarr
(2004)
Classifying RNA pseudoknotted structures.
Theoretical Computer Science, 320 (1), .
(doi:10.1016/j.tcs.2004.03.042).
Abstract
Computational prediction of the minimum free energy (mfe) secondary structure of an RNA molecule from its base sequence is valuable in understanding the structure and function of the molecule. Since the general problem of predicting pseudoknotted secondary structures is NP-hard, several algorithms have been proposed that find the mfe secondary structure from a restricted class of secondary structures. In this work, we order the algorithms by generality of the structure classes that they handle. We provide simple characterizations of the classes of structures handled by four algorithms, as well as linear time methods to test whether a given secondary structure is in three of these classes. We report on the percentage of biological structures from the PseudoBase and Gutell databases that are handled by these three algorithms.
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e-pub ahead of print date: 10 April 2004
Published date: 12 June 2004
Identifiers
Local EPrints ID: 426392
URI: http://eprints.soton.ac.uk/id/eprint/426392
ISSN: 0304-3975
PURE UUID: cf4e1170-a02a-4c4e-830d-13df4f1d7c6c
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Date deposited: 27 Nov 2018 17:30
Last modified: 16 Mar 2024 04:39
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Contributors
Author:
Anne Condon
Author:
Beth Davy
Author:
Baharak Rastegari
Author:
Shelly Zhao
Author:
Finbarr Tarrant
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