A practical O(n log2n) time algorithm for computing the triplet distance on binary trees

The triplet distance is a distance measure that compares two rooted trees on the same set of leaves by enumerating all sub-sets of three leaves and counting how often the induced topologies of the tree are equal or different. We present an algorithm that computes the triplet distance between two roo...

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Vydané v:BMC bioinformatics Ročník 14; číslo Suppl 2; s. S18
Hlavní autori: Sand, Andreas, Brodal, Gerth Stølting, Fagerberg, Rolf, Pedersen, Christian NS, Mailund, Thomas
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: London BioMed Central 21.01.2013
Springer Nature B.V
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Abstract The triplet distance is a distance measure that compares two rooted trees on the same set of leaves by enumerating all sub-sets of three leaves and counting how often the induced topologies of the tree are equal or different. We present an algorithm that computes the triplet distance between two rooted binary trees in time O ( n log 2 n ). The algorithm is related to an algorithm for computing the quartet distance between two unrooted binary trees in time O ( n log n ). While the quartet distance algorithm has a very severe overhead in the asymptotic time complexity that makes it impractical compared to O ( n 2 ) time algorithms, we show through experiments that the triplet distance algorithm can be implemented to give a competitive wall-time running time.
AbstractList The triplet distance is a distance measure that compares two rooted trees on the same set of leaves by enumerating all sub-sets of three leaves and counting how often the induced topologies of the tree are equal or different. We present an algorithm that computes the triplet distance between two rooted binary trees in time O (n log2 n). The algorithm is related to an algorithm for computing the quartet distance between two unrooted binary trees in time O (n log n). While the quartet distance algorithm has a very severe overhead in the asymptotic time complexity that makes it impractical compared to O (n2) time algorithms, we show through experiments that the triplet distance algorithm can be implemented to give a competitive wall-time running time.
The triplet distance is a distance measure that compares two rooted trees on the same set of leaves by enumerating all sub-sets of three leaves and counting how often the induced topologies of the tree are equal or different. We present an algorithm that computes the triplet distance between two rooted binary trees in time O (n log2 n). The algorithm is related to an algorithm for computing the quartet distance between two unrooted binary trees in time O (n log n). While the quartet distance algorithm has a very severe overhead in the asymptotic time complexity that makes it impractical compared to O (n2) time algorithms, we show through experiments that the triplet distance algorithm can be implemented to give a competitive wall-time running time.The triplet distance is a distance measure that compares two rooted trees on the same set of leaves by enumerating all sub-sets of three leaves and counting how often the induced topologies of the tree are equal or different. We present an algorithm that computes the triplet distance between two rooted binary trees in time O (n log2 n). The algorithm is related to an algorithm for computing the quartet distance between two unrooted binary trees in time O (n log n). While the quartet distance algorithm has a very severe overhead in the asymptotic time complexity that makes it impractical compared to O (n2) time algorithms, we show through experiments that the triplet distance algorithm can be implemented to give a competitive wall-time running time.
The triplet distance is a distance measure that compares two rooted trees on the same set of leaves by enumerating all sub-sets of three leaves and counting how often the induced topologies of the tree are equal or different. We present an algorithm that computes the triplet distance between two rooted binary trees in time O ( n log 2 n ). The algorithm is related to an algorithm for computing the quartet distance between two unrooted binary trees in time O ( n log n ). While the quartet distance algorithm has a very severe overhead in the asymptotic time complexity that makes it impractical compared to O ( n 2 ) time algorithms, we show through experiments that the triplet distance algorithm can be implemented to give a competitive wall-time running time.
Doc number: S18 Abstract: The triplet distance is a distance measure that compares two rooted trees on the same set of leaves by enumerating all sub-sets of three leaves and counting how often the induced topologies of the tree are equal or different. We present an algorithm that computes the triplet distance between two rooted binary trees in time O (n log2 n ). The algorithm is related to an algorithm for computing the quartet distance between two unrooted binary trees in time O (n log n ). While the quartet distance algorithm has a very severe overhead in the asymptotic time complexity that makes it impractical compared to O (n2 ) time algorithms, we show through experiments that the triplet distance algorithm can be implemented to give a competitive wall-time running time.
ArticleNumber S18
Author Pedersen, Christian NS
Brodal, Gerth Stølting
Mailund, Thomas
Sand, Andreas
Fagerberg, Rolf
AuthorAffiliation 4 Department of Mathematics and Computer Science, University of Southern Denmark, Denmark
1 Bioinformatics Research Center, Aarhus University, Denmark
2 Department of Computer Science, Aarhus University, Denmark
3 MADALGO, Center for Massive Data Algorithms, a Center of the Danish National Research Foundation, Denmark
5 PUMPKIN, Center for Membrane Pumps in Cells and Disease, a Center of the Danish National Research Foundation, Denmark
AuthorAffiliation_xml – name: 1 Bioinformatics Research Center, Aarhus University, Denmark
– name: 2 Department of Computer Science, Aarhus University, Denmark
– name: 3 MADALGO, Center for Massive Data Algorithms, a Center of the Danish National Research Foundation, Denmark
– name: 4 Department of Mathematics and Computer Science, University of Southern Denmark, Denmark
– name: 5 PUMPKIN, Center for Membrane Pumps in Cells and Disease, a Center of the Danish National Research Foundation, Denmark
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  givenname: Andreas
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  organization: Bioinformatics Research Center, Aarhus University, Department of Computer Science, Aarhus University
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BackLink https://www.ncbi.nlm.nih.gov/pubmed/23368759$$D View this record in MEDLINE/PubMed
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Cites_doi 10.1186/1748-7188-1-16
10.1142/S0219720008003266
10.1142/9781860947995_0013
10.1016/0025-5564(81)90043-2
10.1007/s00453-003-1065-y
10.1093/sysbio/45.3.323
10.1186/1748-7188-6-15
10.1016/j.tcs.2011.08.027
10.1007/BF01908061
10.1093/bioinformatics/bth097
10.2307/2413326
ContentType Journal Article
Copyright Sand et al.; licensee BioMed Central Ltd. 2013 This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License ( ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
2013 Sand et al.; licensee BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright ©2013 Sand et al.; licensee BioMed Central Ltd. 2013 Sand et al.; licensee BioMed Central Ltd.
Copyright_xml – notice: Sand et al.; licensee BioMed Central Ltd. 2013 This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License ( ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
– notice: 2013 Sand et al.; licensee BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
– notice: Copyright ©2013 Sand et al.; licensee BioMed Central Ltd. 2013 Sand et al.; licensee BioMed Central Ltd.
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Keywords Lower Common Ancestor
Brodal
Contractible Edge
Time Algorithm
Binary Tree
Language English
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Biomedical and Life Sciences
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Computational Biology/Bioinformatics
Computer Appl. in Life Sciences
Computer science
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Title A practical O(n log2n) time algorithm for computing the triplet distance on binary trees
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