Algorithms for Computing the Triplet and Quartet Distances for Binary and General Trees

Distance measures between trees are useful for comparing trees in a systematic manner, and several different distance measures have been proposed. The triplet and quartet distances, for rooted and unrooted trees, respectively, are defined as the number of subsets of three or four leaves, respectivel...

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Main Authors: Thomas Mailund, Christian N. S. Pedersen, Rolf Fagerberg, Gerth Stølting Brodal, Morten K. Holt, Jens Johansen, Andreas Sand
Format: Article
Language:English
Published: MDPI AG 2013-09-01
Series:Biology
Subjects:
Online Access:http://www.mdpi.com/2079-7737/2/4/1189
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spelling doaj-d30e0af930834dc9aa81e83c19cb2aa32020-11-24T23:43:11ZengMDPI AGBiology2079-77372013-09-01241189120910.3390/biology2041189Algorithms for Computing the Triplet and Quartet Distances for Binary and General TreesThomas MailundChristian N. S. PedersenRolf FagerbergGerth Stølting BrodalMorten K. HoltJens JohansenAndreas SandDistance measures between trees are useful for comparing trees in a systematic manner, and several different distance measures have been proposed. The triplet and quartet distances, for rooted and unrooted trees, respectively, are defined as the number of subsets of three or four leaves, respectively, where the topologies of the induced subtrees differ. These distances can trivially be computed by explicitly enumerating all sets of three or four leaves and testing if the topologies are different, but this leads to time complexities at least of the order n3 or n4 just for enumerating the sets. The different topologies can be counte dimplicitly, however, and in this paper, we review a series of algorithmic improvements that have been used during the last decade to develop more efficient algorithms by exploiting two different strategies for this; one based on dynamic programming and another based oncoloring leaves in one tree and updating a hierarchical decomposition of the other.http://www.mdpi.com/2079-7737/2/4/1189algorithmic developmenttree comparisontriplet distancequartet distance
collection DOAJ
language English
format Article
sources DOAJ
author Thomas Mailund
Christian N. S. Pedersen
Rolf Fagerberg
Gerth Stølting Brodal
Morten K. Holt
Jens Johansen
Andreas Sand
spellingShingle Thomas Mailund
Christian N. S. Pedersen
Rolf Fagerberg
Gerth Stølting Brodal
Morten K. Holt
Jens Johansen
Andreas Sand
Algorithms for Computing the Triplet and Quartet Distances for Binary and General Trees
Biology
algorithmic development
tree comparison
triplet distance
quartet distance
author_facet Thomas Mailund
Christian N. S. Pedersen
Rolf Fagerberg
Gerth Stølting Brodal
Morten K. Holt
Jens Johansen
Andreas Sand
author_sort Thomas Mailund
title Algorithms for Computing the Triplet and Quartet Distances for Binary and General Trees
title_short Algorithms for Computing the Triplet and Quartet Distances for Binary and General Trees
title_full Algorithms for Computing the Triplet and Quartet Distances for Binary and General Trees
title_fullStr Algorithms for Computing the Triplet and Quartet Distances for Binary and General Trees
title_full_unstemmed Algorithms for Computing the Triplet and Quartet Distances for Binary and General Trees
title_sort algorithms for computing the triplet and quartet distances for binary and general trees
publisher MDPI AG
series Biology
issn 2079-7737
publishDate 2013-09-01
description Distance measures between trees are useful for comparing trees in a systematic manner, and several different distance measures have been proposed. The triplet and quartet distances, for rooted and unrooted trees, respectively, are defined as the number of subsets of three or four leaves, respectively, where the topologies of the induced subtrees differ. These distances can trivially be computed by explicitly enumerating all sets of three or four leaves and testing if the topologies are different, but this leads to time complexities at least of the order n3 or n4 just for enumerating the sets. The different topologies can be counte dimplicitly, however, and in this paper, we review a series of algorithmic improvements that have been used during the last decade to develop more efficient algorithms by exploiting two different strategies for this; one based on dynamic programming and another based oncoloring leaves in one tree and updating a hierarchical decomposition of the other.
topic algorithmic development
tree comparison
triplet distance
quartet distance
url http://www.mdpi.com/2079-7737/2/4/1189
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