Evaluation of Molecular Phylogenetic Trees by an Information-Theoretic Metric.

Understanding phylogenetic relationships among species is fundamental to many biological studies. Constructing phylogenetic trees based on molecular data is important not only for considering the evolution and classification of organisms, but also for understanding how genes retain and transmit information, which forms the basis of life science. However, it is currently difficult to determine which phylogenetic analysis method, including evolutionary models, is most appropriate for the target sequences, and which of the resulting phylogenetic trees most appropriately represents the underlying evolutionary relationships. Here, we propose a method for inferring common ancestral sequences and introduce an information-theoretic metric to provide a unified framework for quantitatively comparing phylogenetic trees based on information transmission between molecular sequences. Our metric can evaluate which phylogenetic tree is optimal from an information-theoretic point of view by determining and comparing the amount of information in phylogenetic trees generated by different methods in terms of the transmission of information between molecular sequences along the evolutionary process. The metric we introduced will facilitate understanding not only the evolution and classification of organisms, but also the phenomena of life that are deeply related to information transmission.