Fast and Accurate Phylogeny Reconstruction Algorithms Based on the Minimum-Evolution Principle
WABI '02 Proceedings of the Second International Workshop on Algorithms in Bioinformatics
The Performance of Neighbor-Joining Algorithms of Phylogeny Recronstruction
COCOON '97 Proceedings of the Third Annual International Conference on Computing and Combinatorics
IEEE Transactions on Information Theory
Accuracy guarantees for phylogeny reconstruction algorithms based on balanced minimum evolution
WABI'10 Proceedings of the 10th international conference on Algorithms in bioinformatics
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For a phylogeny reconstruction problem, Desper and Gascuel [2] proposed Greedy Minimum Evolution algorithm (in short, GME) and Balanced Minimum Evolution algorithm (in short, BME). Both of them are faster than the current major algorithm, Neighbor Joining (in short, NJ); however, less accurate when an input distance matrix has errors. In this paper, we prove that BME has the same optimal robustness to such errors as NJ but GME does not. Precisely, we prove that if the maximum distance error is less than a half of the minimum edge length of the target tree, then BME reconstruct it correctly. On the other hand, there is some distance matrix such that maximum distance error is less than $\frac{2}{\sqrt{n}}$ of the minimum edge length of the target tree, for which GME fails to reconstruct the target tree.