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JCB
2007

Neighbor Joining Algorithms for Inferring Phylogenies via LCA Distances

9 years 5 months ago
Neighbor Joining Algorithms for Inferring Phylogenies via LCA Distances
Reconstructing phylogenetic trees efficiently and accurately from distance estimates is an ongoing challenge in computational biology from both practical and theoretical considerations. We study algorithms which are based on a characterization of edge-weighted trees by distances to LCAs (Least Common Ancestors). This characterization enables a direct application of ultrametric reconstruction techniques to trees which are not necessarily ultrametric.A simple and natural neighbor joining criterion based on this observation is used to provide a family of efficient neighbor-joining algorithms. These algorithms are shown to reconstruct a refinement of the Buneman tree, which implies optimal robustness to noise under criteria defined by Atteson. In this sense, they outperform many popular algorithms such as Saitou and Nei’s NJ. One member of this family is used to provide a new simple version of the 3-approximation algorithm for the closest additive metric under the l∞ norm.A byprod...
Ilan Gronau, Shlomo Moran
Added 15 Dec 2010
Updated 15 Dec 2010
Type Journal
Year 2007
Where JCB
Authors Ilan Gronau, Shlomo Moran
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