The AxML program family for maximum likelihood‐based phylogenetic tree inference

Inference of phylogenetic (evolutionary) trees comprising hundreds or thousands of organisms based on the maximum likelihood criterion is a computationally extremely intensive task. This paper describes the evolution of the AxML program family which provides novel algorithmic as well as technical solutions for the maximum likelihood‐based inference of huge phylogenetic trees. Algorithmic optimizations and a new tree building algorithm yield runtime improvements of a factor greater than 4 compared with fastDNAml and parallel fastDNAml, returning equally good trees at the same time. Various parallel, distributed, and Grid‐based implementations of AxML give the program the capability to acquire the large amount of required computational resources for the inference of huge high‐quality trees.