Reading Evolutionary Biology Group - Current Research
Phylogenetic Inference
We are investigating models of sequence evolution suitable for data that can vary their tempo or rate and mode of evolution from site to site or throughout the phylogenetic tree. We have devised mixture models and covarion based models for gene-sequence, morphological or other data. The techniques are implemented as Markov Chain Monte Carlo methods (including reversible-jump) that find Bayesian posterior distributions of model parameters. They can detect rate variation, heterotachy, so-called invariant sites, and identify the model of sequence evolution that best describes a given site's evolution.