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On the optimality of the neighbor-joining algorithm

Eickmeyer, Kord and Huggins, Peter and Pachter, Lior and Yoshida, Ruriko (2008) On the optimality of the neighbor-joining algorithm. Algorithms for Molecular Biology, 3 . Art. No. 5. ISSN 1748-7188. PMCID PMC2430562. doi:10.1186/1748-7188-3-5.

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The popular neighbor-joining (NJ) algorithm used in phylogenetics is a greedy algorithm for finding the balanced minimum evolution (BME) tree associated to a dissimilarity map. From this point of view, NJ is "optimal" when the algorithm outputs the tree which minimizes the balanced minimum evolution criterion. We use the fact that the NJ tree topology and the BME tree topology are determined by polyhedral subdivisions of the spaces of dissimilarity maps ℛ^(^n _2)_+ to study the optimality of the neighbor-joining algorithm. In particular, we investigate and compare the polyhedral subdivisions for n ≤ 8. This requires the measurement of volumes of spherical polytopes in high dimension, which we obtain using a combination of Monte Carlo methods and polyhedral algorithms. Our results include a demonstration that highly unrelated trees can be co-optimal in BME reconstruction, and that NJ regions are not convex. We obtain the l_2 radius for neighbor-joining for n = 5 and we conjecture that the ability of the neighbor-joining algorithm to recover the BME tree depends on the diameter of the BME tree.

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Pachter, Lior0000-0002-9164-6231
Additional Information:© Eickmeyer et al; licensee BioMed Central Ltd. 2008. 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. Received: 13 November 2007. Accepted: 30 April 2008. Published: 30 April 2008. The authors declare that they have no competing interests.
PubMed Central ID:PMC2430562
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ID Code:74804
Deposited On:07 Mar 2017 00:06
Last Modified:11 Nov 2021 05:30

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