Phylogenetics beyond biology.

Area of Science:

• Evolutionary biology
• Computational phylogenetics
• Cultural evolution

Background:

• Evolutionary processes are observed in biology and human culture, but mechanisms remain unclear.
• Quantifying distances between taxa is crucial for phylogenetic inference but challenging without mechanistic models.
• Incorrect distance measures can lead to inaccurate phylogenetic trees.

Purpose of the Study:

• To address the challenge of phylogenetic inference when evolutionary mechanisms are unknown.
• To develop a method for computing accurate phylogenetic trees from distance data.
• To investigate the impact of distance measure choice on phylogenetic accuracy.

Main Methods:

• Analyzing distortions in metric distances and their effect on phylogenetic trees.
• Utilizing the property that phylogenetic inference requires additive metrics.
• Developing a metric-preserving transformation through an optimization problem.

Main Results:

• Demonstrating that poor distance measures yield incorrect phylogenetic trees.
• Showing that correct phylogeny can be computed if a suitable transformation exists.
• Providing a method to compute the required metric-preserving transformation.

Conclusions:

• Phylogeny reconstruction is well-defined even without a complete mechanistic model of evolution.
• The proposed transformation ensures additivity of distance metrics for accurate phylogenetic inference.
• This work advances computational phylogenetics by providing a robust method for tree reconstruction.