Approximation and Exact Algorithms for RNA Secondary Structure Prediction and Recognition of Stochastic Context-Free Languages

Authors:
Tatsuya Akutsu
Affiliations:
-
Venue:
ISAAC '98 Proceedings of the 9th International Symposium on Algorithms and Computation
Year:
1998

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Abstract

For a basic version (i.e., maximizing the number of base-pairs) of the RNA secondary structure prediction problem and the construction of a parse tree for a stochastic context-free language, O(n3) time algorithms were known. For both problems, this paper shows slightly improved O(n3(log log n)1/2/(log n)1/2) time exact algorithms. Moreover, this paper shows an O(n2.776) time approximation algorithm for the former problem and an O(n2.976 log n) time approximation algorithm for the latter problem, each of which has a guaranteed approximation ratio 1 - Ɛ for any fixed constant Ɛ 0, where the absolute value of the logarithm of the probability is considered as an objective value in the latter problem. Several related results are shown too.