The minimum evolution problem is hard: a link between tree inference and graph clustering problems.

Bastkowski, Sarah; Moulton, Vincent; Spillner, Andreas; Wu, Taoyang · Bioinformatics · 2016

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Abstract

Distance methods are well suited for constructing massive phylogenetic trees. However, the computational complexity for Rzhetsky and Nei's minimum evolution (ME) approach, one of the earliest methods for constructing a phylogenetic tree from a distance matrix, remains open. We show that Rzhetsky and Nei's ME problem is NP-complete, and so probably computationally intractable. We do this by linking the ME problem to a graph clustering problem called the quasi-clique decomposition problem, which has recently also been shown to be NP-complete. We also discuss how this link could potentially open up some useful new connections between phylogenetics and graph clustering.

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