Sentence examples for multiple consensus trees from inspiring English sources

In a recent attempt, Guénoche [ 73] developed a method to tackle the problem of conflicting evolutionary signals by finding multiple consensus trees instead of a network as a method for separating and representing the evolution of diverging genes.

Originally designed as a tool for drawing phylogenetic trees, this new version of Dendroscope is geared toward analyzing multiple trees using both consensus trees and rooted networks.

When a pool of the major rooted triplets is available to present major phylogenetic relationships of all possible three-sequence combinations for multiple sequences, a consensus tree of the major rooted triplets could present the major phylogenetic relationship of all of the involved sequences.

Heuristic ML searches were performed with PAUP* 4.0b10 [34] and involved multiple rounds of TBR branch swapping, alternatively starting from Bayesian consensus trees or from ML trees estimated by the program Phyml 2.4.1 [35].

Strict consensus trees and agreement subtrees [43] were used to examine topological conflicts among multiple most parsimonious trees.

Full consensus trees in Extended Data.

The remaining trees were used to calculate strict consensus trees.

ML trees and MCMC consensus trees were visualized in FigTree (http://tree.bio.ed.ac.uk/software/figtree/).ac.uk/software/figtree/

Consensus trees were calculated with Consense [ 41].

All consensus trees successfully recovered the correct tree topology.

To verify this assumption, we compared the reconstructed network evolutionary histories using two phylogeny inference programs to generate the initial protein trees: MUSCLE (applies multiple sequence alignment and the neighbor-joining method to build the gene trees) and PhyloBayes 3.3 (applies MCMC to sample trees from aligned amino acid sequences and reports the consensus trees).