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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...
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.The length of the branches can depict time or the relative amount of change among organisms. For instance, the branch length might indicate the number of amino acid changes in the sequence that underlies the...
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.The length of the branches can depict time or the relative amount of change among organisms. For instance, the branch length might indicate the number of amino acid changes in the sequence that underlies the...
Microbial Phylogeny01:28

Microbial Phylogeny

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,...
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...
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...

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Updated: Jun 28, 2026

A Practical Guide to Phylogenetics for Nonexperts
12:00

A Practical Guide to Phylogenetics for Nonexperts

Published on: February 5, 2014

Pattern classification of phylogeny signals.

Xiaofei Shi1, Hong Gu, Chris Field

  • 1Dalhousie University. shi@mathstat.dal.ca

Statistical Applications in Genetics and Molecular Biology
|November 4, 2008
PubMed
Summary
This summary is machine-generated.

We introduce minimum entropy clustering (MEC), a novel method for grouping genes using phylogenetic signals. MEC automatically determines the optimal number of gene clusters, enhancing phylogenetic analysis.

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Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin
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Last Updated: Jun 28, 2026

A Practical Guide to Phylogenetics for Nonexperts
12:00

A Practical Guide to Phylogenetics for Nonexperts

Published on: February 5, 2014

An Integrated Approach for Microprotein Identification and Sequence Analysis
09:37

An Integrated Approach for Microprotein Identification and Sequence Analysis

Published on: July 12, 2022

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin
08:57

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Published on: August 14, 2018

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Phylogenetic signal analysis is crucial for understanding gene evolutionary relationships.
  • Existing gene clustering methods often require pre-specification of the number of clusters.
  • Identifying genes with common evolutionary histories is a fundamental challenge in genomics.

Purpose of the Study:

  • To propose a novel Minimum Entropy Clustering (MEC) method for gene clustering.
  • To leverage phylogenetic signals for grouping genes.
  • To develop a method that automatically determines the number of clusters.

Main Methods:

  • The Minimum Entropy Clustering (MEC) method is proposed.
  • Genes are clustered based on their phylogenetic signals.
  • Clustering is driven by the principle of decreasing entropy upon gene concatenation.

Main Results:

  • The MEC method successfully clusters genes that share a common phylogeny.
  • Simulation results demonstrate the effectiveness of the entropy-based approach.
  • Automatic determination of the number of clusters is a key feature and advantage.

Conclusions:

  • Minimum Entropy Clustering (MEC) provides an effective approach for gene clustering based on phylogenetic signals.
  • The automatic selection of cluster numbers simplifies and improves phylogenetic analyses.
  • This method offers a robust tool for exploring evolutionary relationships among genes.