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Related Concept Videos

Phylogenetic Trees03:21

Phylogenetic Trees

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Phylogenetic trees come in many forms. It matters in which sequence the organisms are arranged from the bottom to the top of the tree, but the branches can rotate at their nodes without altering the information. The lines connecting individual nodes can be straight, angled, or even curved.
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Understanding the evolutionary relationships among microorganisms is fundamental to microbial ecology and taxonomy. Phylogenetic trees are essential tools for inferring these relationships, relying primarily on comparative analyses of molecular sequences such as DNA, RNA, or proteins. In microbial studies, these trees typically depict the evolutionary paths of diverse bacterial and archaeal species by mapping genetic differences accumulated over time.Phylogenetic trees are composed of tips,...
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Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
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Phylogeny is concerned with the evolutionary diversification of organisms or groups of organisms. A group of organisms with a name is called a taxon (singular). Taxa (plural) can span different levels of the evolutionary hierarchy. For instance, the group containing all birds is a taxon (comprising the class Aves), and the group of all species of daisies (the genus Bellis) is a taxon. Phylogenies can likewise include just one genus (i.e., depict species relationships) or span an entire kingdom.
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The genomes of eukaryotes are punctuated by long stretches of sequence which do not code for proteins or RNAs. Although some of these regions do contain crucial regulatory sequences, the vast majority of this DNA serves no known function. Typically, these regions of the genome are the ones in which the fastest change, in evolutionary terms, is observed, because there is typically little to no selection pressure acting on these regions to preserve their sequences.
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Updated: Apr 30, 2026

A Practical Guide to Phylogenetics for Nonexperts
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Visual exploration of parameter influence on phylogenetic trees.

Martin Hess, Sebastian Bremm, Stephanie Weissgraeber

    IEEE Computer Graphics and Applications
    |May 9, 2014
    PubMed
    Summary

    This study introduces a visual-analytics method to understand how parameters impact phylogenetic trees. It helps biologists select the most reliable evolutionary trees by clustering similar trees and identifying key parameters.

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    Area of Science:

    • Bioinformatics
    • Computational Biology
    • Evolutionary Biology

    Background:

    • Phylogenetic trees are crucial for understanding evolutionary relationships, inferred from multiple sequence alignments (MSAs).
    • The vast parameter space of MSAs generates numerous potential phylogenetic trees, complicating analysis.
    • Identifying the influence of different parameters on tree construction is essential for accuracy.

    Purpose of the Study:

    • To develop and evaluate a visual-analytics approach for exploring the impact of MSA parameters on phylogenetic tree inference.
    • To enable interactive analysis and automatic identification of parameters significantly affecting tree structures.
    • To facilitate a more reliable selection of phylogenetic trees.

    Main Methods:

    • Hierarchical clustering of phylogenetic trees based on structural similarity.
    • Visualization of tree clusters with associated parameter settings.
    • Interactive exploration of parameter space and its effect on tree topology.

    Main Results:

    • The visual-analytics approach effectively clusters similar phylogenetic trees derived from varying parameter settings.
    • It successfully identifies key parameters that influence tree structure.
    • Application to 16S ribosomal RNA and ion channel protein data demonstrated its utility in parameter impact analysis.

    Conclusions:

    • The proposed visual-analytics method provides an effective way to navigate the complex parameter space of phylogenetic tree inference.
    • It aids researchers in understanding parameter influence, leading to more robust and reliable phylogenetic analyses.
    • This approach enhances the selection of best-fit trees for biological datasets.