Algorithms for local similarity between forests

Zhewei Liang () and Kaizhong Zhang ()
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Zhewei Liang: The University of Western Ontario
Kaizhong Zhang: The University of Western Ontario

Journal of Combinatorial Optimization, 2014, vol. 27, issue 1, No 3, 14-31

Abstract: Abstract An ordered labelled tree is a tree where the left-to-right order among siblings is significant. Ordered labelled forests are sequences of ordered labelled trees. Given two ordered labelled forests $$F$$ F and $$G$$ G , the local forest similarity is to find two sub-forests $$F^{\prime }$$ F ′ and $$G^{\prime }$$ G ′ of $$F$$ F and $$G$$ G respectively such that they are the most similar over all possible $$F^{\prime }$$ F ′ and $$G^{\prime }$$ G ′ . In this paper, we present efficient algorithms for the local forest similarity problem for two types of sub-forests: sibling subforests and closed subforests. Our algorithms can be used to locate the structurally similar regions in RNA secondary structures since RNA molecules’ secondary structures could be represented as ordered labelled forests.

Keywords: Local forest similarity; Closed subforests; Sibling subforests; Forest removing similarity; RNA secondary structure comparison (search for similar items in EconPapers)
Date: 2014
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DOI: 10.1007/s10878-013-9613-0

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