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 |
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| Hlavní autori: | , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
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London
BioMed Central
21.01.2013
Springer Nature B.V |
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| ISSN: | 1471-2105, 1471-2105 |
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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 |
| Author_xml | – sequence: 1 givenname: Andreas surname: Sand fullname: Sand, Andreas organization: Bioinformatics Research Center, Aarhus University, Department of Computer Science, Aarhus University – sequence: 2 givenname: Gerth Stølting surname: Brodal fullname: Brodal, Gerth Stølting organization: Department of Computer Science, Aarhus University, MADALGO, Center for Massive Data Algorithms, a Center of the Danish National Research Foundation – sequence: 3 givenname: Rolf surname: Fagerberg fullname: Fagerberg, Rolf organization: Department of Mathematics and Computer Science, University of Southern Denmark – sequence: 4 givenname: Christian NS surname: Pedersen fullname: Pedersen, Christian NS organization: Bioinformatics Research Center, Aarhus University, Department of Computer Science, Aarhus University, PUMPKIN, Center for Membrane Pumps in Cells and Disease, a Center of the Danish National Research Foundation – sequence: 5 givenname: Thomas surname: Mailund fullname: Mailund, Thomas email: mailund@birc.au.dk organization: Bioinformatics Research Center, Aarhus University |
| 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 |
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| 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. |
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| Keywords | Lower Common Ancestor Brodal Contractible Edge Time Algorithm Binary Tree |
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| References | T Mailund (5607_CR10) 2004; 20 MS Stissing (5607_CR11) 2008; 6 WHE Day (5607_CR4) 1985; 2 DF Robinson (5607_CR1) 1981; 53 GS Brodal (5607_CR13) 2001 J Nielsen (5607_CR7) 2011; 6 MS Stissing (5607_CR6) 2007 MS Bansal (5607_CR9) 2011; 412 D Bryant (5607_CR12) 2000 DE Critchlow (5607_CR2) 1996; 45 GS Brodal (5607_CR5) 2004; 38 GF Estabrook (5607_CR3) 1985; 34 C Christiansen (5607_CR8) 2006; 1 16999860 - Algorithms Mol Biol. 2006 Sep 25;1:16 14962942 - Bioinformatics. 2004 Jul 10;20(10):1636-7 21639882 - Algorithms Mol Biol. 2011 Jun 03;6:15 18324744 - J Bioinform Comput Biol. 2008 Feb;6(1):37-50 |
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| Title | A practical O(n log2n) time algorithm for computing the triplet distance on binary trees |
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