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Updated: Jan 5, 2026

A Practical Guide to Phylogenetics for Nonexperts

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Published on: February 5, 2014

ASPEN, a methodology for reconstructing protein evolution with improved accuracy using ensemble models.

Roman Sloutsky^1,2,3,4, Kristen M Naegle^2,4,5,6

¹Program in Computational and Systems Biology, Washington University, St. Louis, United States.

|October 18, 2019

Summary

This summary is machine-generated.

Selecting diverse protein sequences improves evolutionary model accuracy. Reproducibility of models from subsampled data predicts accuracy, enabling better evolutionary history reconstruction.

Keywords:

computational biology domains ensembles evolutionary biology homology human protein systems biology trees

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Area of Science:

Computational Biology
Evolutionary Biology
Bioinformatics

Background:

Evolutionary reconstruction algorithms model protein or species evolutionary history.
Algorithm accuracy is sensitive to input data quality, including sequence selection and alignment.
Quantifying the accuracy of evolutionary models has been a persistent challenge.

Purpose of the Study:

To investigate if variance from subsampled sequences can identify accurate evolutionary models.
To develop methods for improving the accuracy of evolutionary models.
To assess the relationship between model reproducibility and accuracy.

Main Methods:

Subsampling ortholog sequences to generate multiple datasets.
Inferring hundreds of evolutionary models from these subsampled datasets.
Measuring the reproducibility of model topologies across subsamples.
Developing a meta-algorithm leveraging ensemble consistency for accuracy improvement.

Main Results:

Model reproducibility from 90% sequence subsamples directly correlates with reconstruction accuracy.
A measurable metric for evolutionary model accuracy was identified.
Topologies consistent with ensemble observations demonstrated higher accuracy.

Conclusions:

Subsampling and reproducibility analysis offer a novel approach to assess evolutionary model accuracy.
The developed meta-algorithm enhances evolutionary model accuracy by exploiting ensemble consistency.
This work provides a framework for more reliable evolutionary history reconstruction.