Sentence examples for maximum likelihood optimality from inspiring English sources

Heuristic searches with NJ starting trees were conducted under the maximum likelihood optimality criterion.

Phylogenetic estimates were obtained with a maximum likelihood optimality criterion in PhyML 3.0 [ 32].

Furthermore, we validated the results for both parsimony and maximum likelihood optimality criteria.

Phylogenetic estimates were obtained with a maximum likelihood optimality criterion (PhyML [ 36] and RAxML [ 37]) and Bayesian MCMC methods [ 38].

A phylogenetic analysis using amino acid sequences was conducted with RAxML ver. 7.7.1 [ 69] using the maximum likelihood optimality criterion with a JTT amino acid substitution model.

Phylogenetic analyses based on nucleotides were conducted under the maximum likelihood optimality criterion using the GTR + I + Γ model with 4 rate categories implemented in MrBayes 3.1.2 [ 39] and Garli 0.942 [ 38].

The aligned matrix was analyzed using maximum parsimony (MP) and maximum likelihood (ML) optimality criteria and Bayesian Inference (BI).

The phylogenetic matrix was analyzed using maximum parsimony (MP) and maximum likelihood (ML) optimality criteria.

The phylogeny was inferred under Bayesian and maximum likelihood (ML) optimality criteria as implemented in MrBayes 3.2.2 (Ronquist et al., 2012) and RAxML 7.3 (Stamatakis, 2006), respectively.

Phylogenetic analysis was carried out using the NJ method in MEGA 3.0 program [ 65] and Maximum Likelihood (ML) optimality criteria in PHYML algorithm [ 66].

For each of the seven datasets, we performed phylogenetic tree reconstruction with the maximum likelihood (ML) optimality criterion and Four-cluster Likelihood Mapping (FcLM) at the amino acid level.