Maximum likelihood inference of reticulate evolutionary histories

Maximum likelihood inference of reticulate evolutionary histories.

Hybridization plays an important role in the evolution of certain groups of organisms, adaptation to their environments, and diversification of their genomes. The evolutionary histories of such groups are reticulate, and methods for reconstructing them are still in their infancy and have limited applicability. We present a maximum likelihood method for inferring reticulate evolutionary historie...

How Much Information is Needed to Infer Reticulate Evolutionary Histories?

Phylogenetic networks are a generalization of evolutionary trees and are an important tool for analyzing reticulate evolutionary histories. Recently, there has been great interest in developing new methods to construct rooted phylogenetic networks, that is, networks whose internal vertices correspond to hypothetical ancestors, whose leaves correspond to sampled taxa, and in which vertices with ...

Maximum Likelihood of Evolutionary Trees Is Hard

Maximum likelihood (ML) is an increasingly popular optimality criterion for selecting evolutionary trees (Felsenstein, 1981). Finding optimal ML trees appears to be a very hard computational task, but for tractable cases, ML is the method of choice. In particular, algorithms and heuristics for ML take longer to run than algorithms and heuristics for the second major character based criterion, m...

Local Maximum Likelihood Estimation and Inference

Maximum Likelihood Methods for Phylogenetic Inference

In this article, we provide an overview of maximum likelihood methods for phylogenetic inference. A brief introduction to general maximum likelihood estimation is provided. We define a phylogenetic likelihood, summarize how to compute this likelihood, and then discuss approaches used to maximize the phylogenetic likelihood function. We discuss a property of the maximum likelihood estimation, ca...