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Updated: Jan 22, 2026

Molecular Evolution of the Tre Recombinase

Molecular Evolution of the Tre Recombinase

Published on: May 29, 2008

A Not-So-Long Introduction to Computational Molecular Evolution.

Stéphane Aris-Brosou^1,2, Nicolas Rodrigue^3,4,5

¹Department of Biology, University of Ottawa, Ottawa, ON, Canada. sarisbro@uottawa.ca.

Methods in Molecular Biology (Clifton, N.J.)

|July 7, 2019

Summary

This summary is machine-generated.

This chapter introduces computational molecular evolution, covering likelihood methods, DNA substitution models, and divergence time estimation. It explores advanced models linking population genetics and molecular evolution using diffusion theory.

Keywords:

Bayes Divergence times Likelihood Model choice Phylogenetics

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Molecular Evolution of the Tre Recombinase

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Area of Science:

Computational Biology
Molecular Evolution
Phylogenetics

Background:

Likelihood-based methods are crucial in computational molecular evolution.
Standard DNA substitution models form the basis for phylogenetic analysis.
Understanding model choice is essential for accurate evolutionary inference.

Purpose of the Study:

To provide a concise introduction to computational molecular evolution.
To review key methods including DNA substitution models and divergence time estimation.
To highlight the integration of population genetics and molecular evolution.

Main Methods:

Review of likelihood-based phylogenetic inference.
Discussion of standard and advanced DNA substitution models.
Explanation of divergence time and rate estimation techniques.

Main Results:

Emergence and application of likelihood methods in evolutionary studies.
Development of models linking population genetics and molecular evolution.
Overview of contemporary computational tools and implementations.

Conclusions:

Computational molecular evolution integrates diverse methodologies.
Advanced models offer new insights into evolutionary processes.
The chapter provides a foundation for further exploration in the field.