Bayesian statistical inference of species divergences through time

Abstract

The past decade has seen rapid development of Bayesian statistical methods to analyse the evolution of genome sequences and species traits through time. These methods are now routinely applied to understand evolution in viruses, bacteria, crops and their pests, up to the evolution of the large vertebrate genomes and their fossils (including human). In this project the student will work in data analysis and development of computer tools and mathematical models for Bayesian statistical inference of species divergences. Emphasis will be given to methods that co-analyse complete genomes and trait data.




References:
[1]

dos Reis (2016) Notes on the birth-death prior with fossil calibrations for Bayesian estimation of species divergence times. Philosophical Transactions of the Royal Society B. (in press).

[2]

dos Reis et al. (2016) Bayesian molecular clock dating of species divergences in the genomics era. Nature Reviews Genetics, 17: 71–80.

[3]

dos Reis et al. (2015) Uncertainty in the timing of origin of animals and the limits of precision in molecular timescales. Current Biology, 25: 2939–2950.

[4]

Angelis and dos Reis (2015) The impact of ancestral population size and incomplete lineage sorting on Bayesian estimation of species divergence times. Current Zoology, 61: 874–885.

[5]

dos Reis and Yang (2013) The unbearable uncertainty of divergence time estimation. Journal of Systematics and Evolution, 51: 30–43.


Biological Areas:

Genetics
Evolution

BBSRC Area:

Genes, development and STEM approaches to biology