We considered using RAxML [ 23], a fast and reliable implementation of the maximum likelihood phylogenetic approach and MrBayes [ 24] which implements the much slower but more exhaustive Bayesian approach.
The random tree and the simulated values obtained at the leaf nodes were provided as input to RidgeRace and to implementations of the maximum likelihood and generalized least squares algorithms (Felsenstein, 1985; Hansen, 1997) in the APE package for ancestral character state estimation (Paradis et al., 2004).
Algorithm parameters setting in our implementation includes the maximum evaluations, the crossover probability, and the mutation operator, as shown in Table 7.
The standard implementation of the Maximum Entropy Method (MEM) follows Bryan [1] and deploys a Singular Value Decomposition (SVD) to limit the dimensionality of the underlying solution space apriori.
An implementation of the Maximum Recommended Therapeutic Dose (MRTD) set [26] including name, SMILES, and 166-key fingerprints.
Standard learning methods for such models employ a variety of heuristics applied to the expectation-maximization implementation of the maximum likelihood estimation procedure in order to find the global maximum of the likelihood function.
The generated Bayesian trees served as the basis for the implementation of the maximum likelihood methods of the PAML package of programs [ 41] aiming at detecting adaptive molecular evolution under specific models of codon substitution.
In this context, it has been recently recognized that the use of replica averaging represents an implementation of the maximum entropy principle to incorporate the experimental information into the molecular dynamics simulations.
A bayesian phylogenetic approach was used to infer gene-tree topologies that also served as the basis for the implementation of the maximum likelihood methods of the PAML package ver. 4.3 [ 62].
