Sentence examples for more sophisticated evolutionary from inspiring English sources

Emphasizing again the importance of more sophisticated evolutionary models, Wang and Hickey [ 20] perform a detailed analysis of the codon usage in Oryza.

Despite the sequencing of an increasing number of mammalian genomes and the implementation of more sophisticated evolutionary models using maximum likelihood and Bayesian methodology, the branching order within the mammalian phylum is still not completely resolved.

In and by itself, this does not preclude these genes from being part of the LUCA heritage; however, with this particular HGT event being a virtual certainty, a more sophisticated evolutionary reconstruction approach should have mapped their origin to the common ancestor of bacteria rather than to LUCA.

We hypothesized that an additional factor affecting accuracy is evolutionary distance measure used, although it was not clear a priori what the effect would be, as more sophisticated evolutionary models reduce distance estimation bias, but also increase the variance of the estimate [ 28].

More sophisticated evolutionary models such as the heterogenous CAT model, which accounts for among-site heterogeneity (Lartillot and Philippe 2004), and the derived CAT-BP model, which also accounts for lineage-specific compositional heterogeneities (Blanquart and Lartillot 2008), can lessen the effects of compositional biases.

Rapidly increasing computer power has allowed the use of more sophisticated algorithmic designs and evolutionary methods.

Considering that the grid search does not always provide the optimal set of parameters [74], more sophisticated algorithms based on evolutionary programming can be used thus contributing even more accurate models.

This newly constructed genetic map of Lu. angustifolius involved a significantly greater number of markers and a more sophisticated mapping approach (the evolutionary optimization strategy) compared with the two previous maps.

More sophisticated methods for reconstruction of evolutionary scenarios are, mostly, different maximum likelihood (ML) and mixed parsimony/ML models [ 40- 43].

27 Other ways to improve the prediction accuracy include the utilization of evolutionary information, more sophisticated models of covariance scoring, and training data for more accurate pairing thresholds.

This strategy may identify as few as 15% of genes that are known to have evolutionary relationship; a more sophisticated strategy based on linking by intermediate sequences a strategy that we also adopt may increase the ability to recognize genes evolutionary relationship by 70% [ 7].