Sentence examples for most likely tree from inspiring English sources
Maximum likelihood methods seek to identify the most likely tree, given the available data.
For all combinations of markers a single most likely tree was estimated in addition to running 200 250 bootstrap replicates depending on the marker set.
Both the Bayesian consensus tree shown in Figure 3, the most parsimonious tree (73 steps in length) and the most likely tree (–ln likelihood = 922.64) had identical topologies (see Figure 3 for branch support values).
To determine the most likely tree topology, the full aa and codon alignments were analyzed using phylogenetic programs, and then re-examined after removal of the signal peptides, and polyserine domain which showed the least consensus.
The tree topology and branch lengths of the most likely tree obtained were used as input for CONTINUOUS, a computer program that implements the generalized least squares (GLS) model for across-species analysis of comparative data [31], [32].
The most likely tree had a –ln likelihood score of 8851.96, and differed from the tree in Figure 2 and the most parsimonious trees by poorly supported branches within V. dahliae (see Figure 2 for likelihood branch supports).
Then it statistically compares the most likely trees from two sentences to see if they match.
We kept 100 most likely trees for our analysis to account for the uncertainty associated with phylogenetic inference.
The maximum likelihood tree (ML tree), the most parsimonious tree (MP tree), and the most likely trees under the constrained conditions.
A consensus tree was constructed from the ML tree by removing bipartitions found in fewer than 50% of the other most likely trees.
These analyses were carried out for three kinds of tree sets obtained by individual analyses of each of the three regions: (1) all most parsimonious trees recovered in maximum parsimony analyses, (2) all most likely trees recovered in maximum likelihood analyses, and (3) 100 bayesian trees recovered in Bayesian inference of phylogeny.
