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Related Concept Videos

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,...
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

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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.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...
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...
Phylogeny01:23

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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...
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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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A Practical Guide to Phylogenetics for Nonexperts
12:00

A Practical Guide to Phylogenetics for Nonexperts

Published on: February 5, 2014

Time and memory efficient likelihood-based tree searches on phylogenomic alignments with missing data.

Alexandros Stamatakis1, Nikolaos Alachiotis

  • 1The Exelixis Lab (I12), Department of Computer Science, Technische Universität München, Boltzmannstr. 3, D-85748, Garching b. München, Germany. stamatak@cs.tum.edu

Bioinformatics (Oxford, England)
|June 10, 2010
PubMed
Summary
This summary is machine-generated.

This study introduces a novel mechanism to significantly reduce memory usage and accelerate computational time in large-scale phylogenomic analyses, especially those with substantial missing data. The method enhances efficiency for maximum likelihood and Bayesian phylogenetic analyses.

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Last Updated: Jun 12, 2026

A Practical Guide to Phylogenetics for Nonexperts
12:00

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Published on: February 5, 2014

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08:57

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Published on: August 14, 2018

The ITS2 Database
16:17

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Published on: March 12, 2012

Area of Science:

  • Computational Biology
  • Bioinformatics
  • Evolutionary Biology

Background:

  • Large-scale phylogenomic analyses face challenges due to massive datasets with extensive missing data (gappyness >90%).
  • Existing computational methods struggle with memory footprints and processing time for such datasets.

Purpose of the Study:

  • To develop and implement an efficient mechanism for reducing memory usage in phylogenomic analyses.
  • To accelerate tree searches using subtree pruning and re-grafting moves in the presence of missing data.

Main Methods:

  • A generally applicable mechanism for reducing memory footprints in likelihood-based (ML, Bayesian) phylogenomic analyses was developed.
  • Algorithmic rules were introduced for efficient tree searches using subtree pruning and re-grafting.

Main Results:

  • Achieved a memory footprint reduction from 9 GB to 1 GB on a dataset with 2177 taxa and 90% gappyness.
  • Demonstrated a 11-fold speedup in optimizing ML model parameters and a 16-fold acceleration of the Subtree Pruning Regrafting tree search.

Conclusions:

  • The developed approach significantly improves computational efficiency (CPU time and memory) by up to an order of magnitude for phylogenomic analyses.
  • This method is crucial for handling the increasing size and complexity of molecular datasets in evolutionary studies.