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Unrooted tree reconciliation: a unified approach.

Pawel Górecki¹, Oliver Eulenstein, Jerzy Tiuryn

¹Department of Mathematics, Informatics and Mechanics, University of Warsaw, Warsaw, Mazowieckie 02-097, Poland.

IEEE/ACM Transactions on Computational Biology and Bioinformatics

|August 10, 2013

Summary

This study introduces a new "consistency condition" for comparing evolutionary trees, simplifying the identification of optimal rootings. This condition ensures efficient linear-time solutions for phylogenetic tree comparison functions, improving computational methods.

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Area of Science:

Computational Biology
Phylogenetics
Evolutionary Biology

Background:

Tree comparison functions are crucial for analyzing evolutionary relationships.
Rooting unrooted trees to minimize comparison costs is computationally intensive.
The plateau property simplifies finding optimal rootings but is proven for few functions.

Purpose of the Study:

Introduce a general "consistency condition" for tree comparison functions.
Develop linear-time algorithms for identifying optimal rootings and costs for consistent functions.
Explore relationships between consistent functions and their plateaus.

Main Methods:

Defined the "consistency condition" as a sufficient criterion for the plateau property.
Developed general linear-time algorithms applicable to consistent functions.
Introduced a formal language of Boolean costs to identify consistent functions.
Utilized empirical and simulation studies for performance evaluation.

Main Results:

The consistency condition guarantees the plateau property for a broader class of functions.
General linear-time solutions were developed for consistent functions.
Demonstrated that the duplication-loss function's plateau is contained within other consistent functions' plateaus.
Validated the efficiency of the new algorithms in practice.

Conclusions:

The consistency condition provides a unified framework for efficient phylogenetic tree comparison.
The developed methods offer significant computational advantages for analyzing evolutionary trees.
This work advances the understanding and computational treatment of tree comparison functions in phylogenetics.