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Related Concept Videos

Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

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...
Gene Evolution - Fast or Slow?02:05

Gene Evolution - Fast or Slow?

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.
In contrast, regions which code...
Gene Evolution - Fast or Slow?02:05

Gene Evolution - Fast or Slow?

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.
In contrast, regions which code...
Phylogenetic Trees03:21

Phylogenetic Trees

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.
Phylogenetic Trees03:21

Phylogenetic Trees

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.
Phylogeny01:23

Phylogeny

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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Related Experiment Video

Updated: May 14, 2026

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin
08:57

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Published on: August 14, 2018

LSHPlace: fast phylogenetic placement using locality-sensitive hashing.

Daniel G Brown1, Jakub Truszkowski

  • 1David R. Cheriton School of Computer Science, University of Waterloo, Waterloo ON N2L 3G1, Canada. browndg@uwaterloo.ca

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
|February 21, 2013
PubMed
Summary
This summary is machine-generated.

This study introduces a fast phylogenetic placement method for analyzing numerous next-generation sequencing reads. The approach significantly speeds up sequence placement onto existing phylogenetic trees with minimal accuracy loss.

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A Practical Guide to Phylogenetics for Nonexperts
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Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
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Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

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Related Experiment Videos

Last Updated: May 14, 2026

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin
08:57

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Published on: August 14, 2018

A Practical Guide to Phylogenetics for Nonexperts
12:00

A Practical Guide to Phylogenetics for Nonexperts

Published on: February 5, 2014

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
08:03

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Published on: December 7, 2021

Area of Science:

  • Computational Biology
  • Bioinformatics
  • Phylogenetics

Background:

  • Phylogenetic placement is crucial for analyzing large sequence datasets, especially from next-generation sequencing (NGS).
  • Existing methods can be computationally intensive, limiting the scale of analyses.
  • Accurate placement of new sequences onto established phylogenetic trees is essential for evolutionary studies.

Purpose of the Study:

  • To develop a highly efficient method for phylogenetic placement of numerous sequences onto existing phylogenetic trees.
  • To adapt existing phylogenetic tree inference techniques for rapid sequence placement.
  • To enable the analysis of larger NGS datasets than previously feasible.

Main Methods:

  • Adaptation of ancestral sequence reconstruction techniques.
  • Application of locality-sensitive hashing for efficient data indexing and retrieval.
  • Integration of these methods for high-fidelity phylogenetic placement.

Main Results:

  • Achieved runtimes two orders of magnitude faster than current phylogenetic placement programs.
  • Demonstrated high fidelity in placing new sequences onto existing phylogenetic trees.
  • Observed a modest tradeoff in accuracy compared to slower methods.

Conclusions:

  • The developed method offers a significant speedup for phylogenetic placement of NGS reads.
  • This advancement allows for the analysis of substantially larger datasets in phylogenetic studies.
  • The approach opens new possibilities for large-scale genomic and evolutionary research.