Brody Steven Sandel

Computing the Skewness of the Phylogenetic Mean Pairwise Distance in Linear Time

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Standard

Computing the Skewness of the Phylogenetic Mean Pairwise Distance in Linear Time. / Tsirogiannis, Constantinos; Sandel, Brody Steven.

Algorithms in Bioinformatics: 13th International Workshop, WABI 2013, Sophia Antipolis, France, September 2-4, 2013. Proceedings. red. / Aaron Darling; Jens Stoye. Springer VS, 2013. s. 170-184 (Lecture Notes in Computer Science, Bind 8126).

Publikation: Bidrag til bog/antologi/rapport/proceedingKonferencebidrag i proceedingsForskningpeer review

Harvard

Tsirogiannis, C & Sandel, BS 2013, Computing the Skewness of the Phylogenetic Mean Pairwise Distance in Linear Time. i A Darling & J Stoye (red), Algorithms in Bioinformatics: 13th International Workshop, WABI 2013, Sophia Antipolis, France, September 2-4, 2013. Proceedings. Springer VS, Lecture Notes in Computer Science, bind 8126, s. 170-184, 13th International Workshop, WABI 2013, Sophia Antipolis, Frankrig, 02/09/2013. https://doi.org/10.1007/978-3-642-40453-5_14

APA

Tsirogiannis, C., & Sandel, B. S. (2013). Computing the Skewness of the Phylogenetic Mean Pairwise Distance in Linear Time. I A. Darling, & J. Stoye (red.), Algorithms in Bioinformatics: 13th International Workshop, WABI 2013, Sophia Antipolis, France, September 2-4, 2013. Proceedings (s. 170-184). Springer VS. Lecture Notes in Computer Science, Bind. 8126 https://doi.org/10.1007/978-3-642-40453-5_14

CBE

Tsirogiannis C, Sandel BS. 2013. Computing the Skewness of the Phylogenetic Mean Pairwise Distance in Linear Time. Darling A, Stoye J, red. I Algorithms in Bioinformatics: 13th International Workshop, WABI 2013, Sophia Antipolis, France, September 2-4, 2013. Proceedings. Springer VS. s. 170-184. (Lecture Notes in Computer Science, Bind 8126). https://doi.org/10.1007/978-3-642-40453-5_14

MLA

Tsirogiannis, Constantinos og Brody Steven Sandel "Computing the Skewness of the Phylogenetic Mean Pairwise Distance in Linear Time". og Darling, Aaron Stoye, Jens (red.). Algorithms in Bioinformatics: 13th International Workshop, WABI 2013, Sophia Antipolis, France, September 2-4, 2013. Proceedings. Springer VS. (Lecture Notes in Computer Science, Bind 8126). 2013, 170-184. https://doi.org/10.1007/978-3-642-40453-5_14

Vancouver

Tsirogiannis C, Sandel BS. Computing the Skewness of the Phylogenetic Mean Pairwise Distance in Linear Time. I Darling A, Stoye J, red., Algorithms in Bioinformatics: 13th International Workshop, WABI 2013, Sophia Antipolis, France, September 2-4, 2013. Proceedings. Springer VS. 2013. s. 170-184. (Lecture Notes in Computer Science, Bind 8126). https://doi.org/10.1007/978-3-642-40453-5_14

Author

Tsirogiannis, Constantinos ; Sandel, Brody Steven. / Computing the Skewness of the Phylogenetic Mean Pairwise Distance in Linear Time. Algorithms in Bioinformatics: 13th International Workshop, WABI 2013, Sophia Antipolis, France, September 2-4, 2013. Proceedings. red. / Aaron Darling ; Jens Stoye. Springer VS, 2013. s. 170-184 (Lecture Notes in Computer Science, Bind 8126).

Bibtex

@inproceedings{2e0bd3e52bf44213a9a69517126e9047,
title = "Computing the Skewness of the Phylogenetic Mean Pairwise Distance in Linear Time",
abstract = "The phylogenetic Mean Pairwise Distance (MPD) is one of the most popular measures for computing the phylogenetic distance between a given group of species. More specifically, for a phylogenetic tree T and for a set of species R represented by a subset of the leaf nodes of T , the MPD of R is equal to the average cost of all possible simple paths in T that connect pairs of nodes in R.Among other phylogenetic measures, the MPD is used as a tool for deciding if the species of a given group R are closely related. To do this, it is important to compute not only the value of the MPD for this group but also the expectation, the variance, and the skewness of this metric. Although efficient algorithms have been developed for computing the expectation and the variance the MPD, there has been no approach so far for computing the skewness of this measure.In the present work we describe how to compute the skewness of the MPD on a tree T optimally, in Θ(n) time; here n is the size of the tree T . So far this is the first result that leads to an exact, let alone efficient, computation of the skewness for any popular phylogenetic distance measure. Moreover, we show how we can compute in Θ(n) time several interesting quantities in T that can be possibly used as building blocks for computing efficiently the skewness of other phylogenetic measures.",
author = "Constantinos Tsirogiannis and Sandel, {Brody Steven}",
year = "2013",
doi = "10.1007/978-3-642-40453-5_14",
language = "English",
isbn = "978-3-642-40452-8",
pages = "170--184",
editor = "Aaron Darling and Jens Stoye",
booktitle = "Algorithms in Bioinformatics",
publisher = "Springer VS",

}

RIS

TY - GEN

T1 - Computing the Skewness of the Phylogenetic Mean Pairwise Distance in Linear Time

AU - Tsirogiannis, Constantinos

AU - Sandel, Brody Steven

PY - 2013

Y1 - 2013

N2 - The phylogenetic Mean Pairwise Distance (MPD) is one of the most popular measures for computing the phylogenetic distance between a given group of species. More specifically, for a phylogenetic tree T and for a set of species R represented by a subset of the leaf nodes of T , the MPD of R is equal to the average cost of all possible simple paths in T that connect pairs of nodes in R.Among other phylogenetic measures, the MPD is used as a tool for deciding if the species of a given group R are closely related. To do this, it is important to compute not only the value of the MPD for this group but also the expectation, the variance, and the skewness of this metric. Although efficient algorithms have been developed for computing the expectation and the variance the MPD, there has been no approach so far for computing the skewness of this measure.In the present work we describe how to compute the skewness of the MPD on a tree T optimally, in Θ(n) time; here n is the size of the tree T . So far this is the first result that leads to an exact, let alone efficient, computation of the skewness for any popular phylogenetic distance measure. Moreover, we show how we can compute in Θ(n) time several interesting quantities in T that can be possibly used as building blocks for computing efficiently the skewness of other phylogenetic measures.

AB - The phylogenetic Mean Pairwise Distance (MPD) is one of the most popular measures for computing the phylogenetic distance between a given group of species. More specifically, for a phylogenetic tree T and for a set of species R represented by a subset of the leaf nodes of T , the MPD of R is equal to the average cost of all possible simple paths in T that connect pairs of nodes in R.Among other phylogenetic measures, the MPD is used as a tool for deciding if the species of a given group R are closely related. To do this, it is important to compute not only the value of the MPD for this group but also the expectation, the variance, and the skewness of this metric. Although efficient algorithms have been developed for computing the expectation and the variance the MPD, there has been no approach so far for computing the skewness of this measure.In the present work we describe how to compute the skewness of the MPD on a tree T optimally, in Θ(n) time; here n is the size of the tree T . So far this is the first result that leads to an exact, let alone efficient, computation of the skewness for any popular phylogenetic distance measure. Moreover, we show how we can compute in Θ(n) time several interesting quantities in T that can be possibly used as building blocks for computing efficiently the skewness of other phylogenetic measures.

U2 - 10.1007/978-3-642-40453-5_14

DO - 10.1007/978-3-642-40453-5_14

M3 - Article in proceedings

SN - 978-3-642-40452-8

SP - 170

EP - 184

BT - Algorithms in Bioinformatics

A2 - Darling, Aaron

A2 - Stoye, Jens

PB - Springer VS

ER -