Algorithms for local similarity between forests

被引：0
|
作者：
Liang, Zhewei [1 ]
Zhang, Kaizhong [1 ]
机构：
[1] Univ Western Ontario, Dept Comp Sci, London, ON N6A 5B7, Canada
来源：
JOURNAL OF COMBINATORIAL OPTIMIZATION | 2014年 / 27卷 / 01期
关键词：
Local forest similarity; Closed subforests; Sibling subforests; Forest removing similarity; RNA secondary structure comparison; ALIGNMENT; DISTANCE; TREES;
D O I：
10.1007/s10878-013-9613-0
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
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 and , the local forest similarity is to find two sub-forests and of and respectively such that they are the most similar over all possible and . 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.
引用
收藏
页码：14 / 31
页数：18
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