Minimum message length encoding, evolutionary trees and multiple-alignment

Abstract

A method of Bayesian inference known as minimum message length encoding is applied to the inference of an evolutionary-tree and to multiple-alignment for k>or=2 strings. It allows the posterior odds-ratio of two competing hypotheses, for example two trees, to be calculated. A tree that is a good hypothesis forms the basis of a short message describing the strings. The mutation process is modelled by a finite-state machine. It is seen that tree inference and multiple-alignment are intimately connected.<>