Please use this identifier to cite or link to this item:
|Title:||Predicting RNA Secondary Structures with Arbitrary Pseudoknots by Maximizing the Number of Stacking Pairs|
RNA secondary structures
|Citation:||Ieong, S., Kao, M.-Y., Lam, T.-W., Sung, W.-K., Yiu, S.-M. (2003). Predicting RNA Secondary Structures with Arbitrary Pseudoknots by Maximizing the Number of Stacking Pairs. Journal of Computational Biology 10 (6) : 981-995. ScholarBank@NUS Repository. https://doi.org/10.1089/106652703322756186|
|Abstract:||The 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 handle only 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(n3) 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.|
|Source Title:||Journal of Computational Biology|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Feb 20, 2019
WEB OF SCIENCETM
checked on Dec 11, 2017
checked on Feb 2, 2019
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.