Abstract
We present three heuristic strategies for folding RNA sequences into secondary structures including kissing hairpin motifs. The new idea is to construct a kissing hairpin motif from an overlay of two simple canonical pseudoknots. The difficulty is that the overlay does not satisfy Bellman’s Principle of Optimality, and the kissing hairpin cannot simply be built from optimal pseudoknots. Our strategies have time/space complexities of O(n 4) / O(n 2), O(n 4) / O(n 3), and O(n 5) / O(n 2). All strategies have been implemented in the program pKiss and were evaluated against known structures. Surprisingly, our simplest strategy performs best. As it has the same complexity as the previous algorithm for simple pseudoknots, the overlay idea opens a way to construct a variety of practically useful algorithms for pseudoknots of higher topological complexity within O(n 4) time and O(n 2) space.
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Keywords
- Minimum Free Energy
- Nest Structure
- Human Coronavirus
- Pseudoknotted Structure
- Minimum Free Energy Structure
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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Theis, C., Janssen, S., Giegerich, R. (2010). Prediction of RNA Secondary Structure Including Kissing Hairpin Motifs. In: Moulton, V., Singh, M. (eds) Algorithms in Bioinformatics. WABI 2010. Lecture Notes in Computer Science(), vol 6293. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15294-8_5
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DOI: https://doi.org/10.1007/978-3-642-15294-8_5
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