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Updated: Mar 31, 2026

A Practical Guide to Phylogenetics for Nonexperts

A Practical Guide to Phylogenetics for Nonexperts

Published on: February 5, 2014

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

Sarah Bastkowski¹, Vincent Moulton², Andreas Spillner³

¹The Genome Analysis Centre, Norwich, UK.

Bioinformatics (Oxford, England)

|October 27, 2015

Summary

This summary is machine-generated.

The computational complexity of constructing phylogenetic trees using Rzhetsky and Nei's minimum evolution (ME) method is NP-complete. This finding suggests the method is likely computationally intractable for large datasets.

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Published on: February 15, 2017

Area of Science:

Computational Biology
Phylogenetics
Graph Theory

Background:

Distance methods are effective for building large phylogenetic trees.
The computational complexity of Rzhetsky and Nei's minimum evolution (ME) method for phylogenetic tree construction from distance matrices was previously undetermined.

Purpose of the Study:

To determine the computational complexity of Rzhetsky and Nei's minimum evolution (ME) problem.
To establish the tractability of ME-based phylogenetic tree construction.

Main Methods:

Linked the minimum evolution (ME) problem to the quasi-clique decomposition problem in graph theory.
Leveraged the recently established NP-completeness of the quasi-clique decomposition problem.

Main Results:

Demonstrated that the Rzhetsky and Nei minimum evolution (ME) problem is NP-complete.
This implies the ME problem is likely computationally intractable for large-scale phylogenetic analyses.

Conclusions:

The computational intractability of the ME problem has significant implications for phylogenetic tree construction.
The established link between ME and graph clustering may foster new interdisciplinary research avenues.