Alberto Fernández, Natàlia Segura-Alabart, Francesc Serratosa
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引用次数: 0
Abstract
Results from phylogenetic analyses that study the evolution of species according to their biological characteristics are frequently structured as phylogenetic trees. One of the most widely used methods for reconstructing them is the distance-based method known as the neighbor-joining (NJ) algorithm. It is known that the NJ algorithm can produce different phylogenetic trees depending on the order of the taxa in the input matrix of evolutionary distances, because the method only yields bifurcating branches or dichotomies. According to this, results and conclusions published in articles that only calculate one of the possible dichotomic phylogenetic trees are somehow biased. We have generalized the formulas used in the NJ algorithm to cope with Multifurcating branches or polytomies, and we have called this new variant of the method the multifurcating neighbor-joining (MFNJ) algorithm. Instead of the dichotomic phylogenetic trees reconstructed by the NJ algorithm, the MFNJ algorithm produces polytomic phylogenetic trees. The main advantage of using the MFNJ algorithm is that only one phylogenetic tree can be obtained, which makes the experimental section of any study completely reproducible and unbiased to external issues such as the input order of taxa.
期刊介绍:
Journal of Molecular Evolution covers experimental, computational, and theoretical work aimed at deciphering features of molecular evolution and the processes bearing on these features, from the initial formation of macromolecular systems through their evolution at the molecular level, the co-evolution of their functions in cellular and organismal systems, and their influence on organismal adaptation, speciation, and ecology. Topics addressed include the evolution of informational macromolecules and their relation to more complex levels of biological organization, including populations and taxa, as well as the molecular basis for the evolution of ecological interactions of species and the use of molecular data to infer fundamental processes in evolutionary ecology. This coverage accommodates such subfields as new genome sequences, comparative structural and functional genomics, population genetics, the molecular evolution of development, the evolution of gene regulation and gene interaction networks, and in vitro evolution of DNA and RNA, molecular evolutionary ecology, and the development of methods and theory that enable molecular evolutionary inference, including but not limited to, phylogenetic methods.