Predicting RNA Secondary Structures with Arbitrary Pseudoknots by Maximizing the Number of Stacking Pairs

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dc.creatorIeong, Samuel
dc.creatorKao, Ming-Yang
dc.creatorLam, Tak-Wah
dc.creatorSung, Wing-Kin
dc.creatorYiu, Siu-Ming
dc.date2001-11-20
dc.date.accessioned2026-07-07T03:17:58Z
dc.date.available2026-07-07T03:17:58Z
dc.descriptionThe paper investigates the computational problem of predicting RNA secondary structures. The general belief is that allowing pseudoknots makes the problem hard. Existing polynomial-time algorithms are heuristic algorithms with no performance guarantee and can only handle limited types of pseudoknots. In this paper we initiate the study of predicting RNA secondary structures with a maximum number of stacking pairs while allowing arbitrary pseudoknots. We obtain two approximation algorithms with worst-case approximation ratios of 1/2 and 1/3 for planar and general secondary structures,respectively. For an RNA sequence of $n$ bases, the approximation algorithm for planar secondary structures runs in $O(n^3)$ time while that for the general case runs in linear time. Furthermore, we prove that allowing pseudoknots makes it NP-hard to maximize the number of stacking pairs in a planar secondary structure. This result is in contrast with the recent NP-hard results on psuedoknots which are based on optimizing some general and complicated energy functions.
dc.descriptionA preliminary version of this work appeared in Proceedings of the IEEE International Symposium on Bio-Informatics & Biomedical Engineering (BIBE 2001), Washington, DC, 2001
dc.identifierhttps://arxiv.org/abs/cs/0111051
dc.identifierhttp://arxiv.org/abs/cs/0111051
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/30928
dc.subjectComputational Engineering, Finance, and Science
dc.subjectData Structures and Algorithms
dc.subjectQuantitative Biology
dc.subjectF2.2; G2.3; J.3
dc.titlePredicting RNA Secondary Structures with Arbitrary Pseudoknots by Maximizing the Number of Stacking Pairs
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