Despite recent advances achieved by application of high-performance computing methods
and novel algorithmic techniques to maximum likelihood (ML)-based inference programs …

Inference of phylogenetic trees using the maximum likelihood (ML) method is NP-hard.
Furthermore, the computation of the likelihood function for huge trees of more than 1,000 …

Bioinformatics and Computational Biology are fields that requires skills from a variety of
fields to enable the gathering, storing, handling, analyzing, interpreting, and spreading of …

Even when the maximum likelihood (ML) tree is a better estimate of the true phylogenetic
tree than those produced by other methods, the result of a poor ML search may be no better …

Background The rapid accumulation of molecular sequence data, driven by novel wet-lab
sequencing technologies, poses new challenges for large-scale maximum likelihood-based …

A group of agents can be used to perform patrolling tasks in a variety of domains ranging
from computer network administration to computer wargame simulations. The quality of the …

Inference of phylogenetic trees comprising thousands of organisms based on the maximum
likelihood method is computationally expensive. A new program RAxML-SA (Randomized …

Background Understanding the evolutionary relationships among species based on their
genetic information is one of the primary objectives in phylogenetic analysis. Reconstructing …

The reconstruction of phylogenetic (evolutionary) trees from molecular sequence data is a
comparatively old problem in bioinformatics, given that Joe Felsenstein's seminal paper [12] …

Phylogenetic trees are important in biology since their applications range from determining
protein function to understanding the evolution of species. Maximum Likelihood (ML) is a …