Linear Time Algorithm for Parsing RNA Secondary Structure
Part of the
Lecture Notes in Computer Science
book series (LNCS, volume 3692)
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.
KeywordsSecondary Structure Dynamic Programming Algorithm Closed Region Band Region Base Index
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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