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Updated: Jun 5, 2026

A Practical Guide to Phylogenetics for Nonexperts

A Practical Guide to Phylogenetics for Nonexperts

Published on: February 5, 2014

Model selection in Bayesian segmentation of multiple DNA alignments.

Christopher Oldmeadow¹, Jonathan M Keith

¹Centre for Clinical Epidemiology and Biostatistics, University of Newcastle, NSW, Victoria, Australia. christopher.oldmeadow@newcastle.edu.au

Bioinformatics (Oxford, England)

|January 7, 2011

Summary

This summary is machine-generated.

Determining the number of evolutionary rate modes is crucial for identifying functional genomic elements. This study finds six distinct classes of evolutionary rates, robust across different species alignments.

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Creating and Applying a Reference to Facilitate the Discussion and Classification of Proteins in a Diverse Group

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Published on: August 16, 2017

Area of Science:

Evolutionary biology
Genomics
Bioinformatics

Background:

Multiple sequence alignment analysis provides insights into evolution and functional genomic regions.
Understanding evolutionary rate distributions is key to distinguishing functional from non-functional genomic elements.
A simple binary classification of evolutionary rates is insufficient; multi-modal distributions are expected.

Purpose of the Study:

To evaluate information criterion approaches for determining the number of modes in evolutionary rate distributions.
To assess the robustness of these methods using simulations and real data.
To identify distinct classes of evolutionary rates within genomic data.

Main Methods:

Utilized information criterion approaches derived from Markov Chain Monte Carlo (MCMC) simulations.
Employed a Deviance Information Criterion (DIC) approximation for robustness.
Analyzed multiple sequence alignments from primate species and mouse.

Main Results:

Information criteria approximations did not produce superfluous modes in conservation estimations.
Identified six distinct classes of evolutionary rates.
The identified classes were robust across different multiple alignments.

Conclusions:

The multi-modal nature of evolutionary rates can be effectively determined using information criteria.
Six distinct classes of evolutionary rates are evident in the analyzed genomic data.
These findings aid in distinguishing functional genomic elements based on evolutionary conservation patterns.