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Live neighbor-joining.

Guilherme P Telles1, Graziela S Araújo2, Maria E M T Walter3

  • 1Instituto de Computação, Universidade Estadual de Campinas, Cidade Universitária, Campinas, 13083-852, Brazil.

BMC Bioinformatics
|May 18, 2018
PubMed
Summary
This summary is machine-generated.

Live Neighbor-Joining builds phylogenies including living taxa. This method offers new insights into viral, bacterial, and non-biological data relationships, expanding phylogenetic applications.

Keywords:
Live phylogenyNeighbor-joiningPhylogeny

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Area of Science:

  • Phylogenetics
  • Bioinformatics
  • Computational Biology

Background:

  • Traditional phylogenetic reconstruction results in trees with hypothetical ancestors as internal nodes.
  • Live phylogeny allows for the coexistence of ancestral and living taxa, where internal nodes can represent living organisms.
  • The Neighbor-Joining heuristic is a widely used method for phylogenetic reconstruction.

Purpose of the Study:

  • To introduce Live Neighbor-Joining, a novel heuristic for constructing live phylogenies.
  • To explore the application of Live Neighbor-Joining in analyzing viral, bacterial, and non-biological datasets.
  • To demonstrate the utility of live phylogenies in visualizing relationships within diverse data types.

Main Methods:

  • Development of the Live Neighbor-Joining heuristic.
  • Application of the heuristic to viral genome datasets.
  • Testing the method on bacterial genomes, images, and text datasets.

Main Results:

  • Live Neighbor-Joining successfully constructed live phylogenies for viral genomes, revealing alternative hypotheses of relationships.
  • The method was applied to bacterial genomes, generating alternative phylogenetic hypotheses.
  • Analysis of image and text datasets demonstrated the visualization of content similarity through live phylogenies.

Conclusions:

  • Live Neighbor-Joining provides alternative phylogenetic hypotheses for RNA virus genomes and bacterial genomes.
  • The heuristic is applicable to non-biological data, such as images and texts, for exploring content similarity.
  • This method broadens the scope of phylogenetic analysis to include scenarios with coexisting ancestral and living taxa.