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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...
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Conservation of Protein Domains Over Different Proteins02:26

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Related Experiment Video

Updated: Jun 29, 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 model of evolution and structure for multiple sequence alignment.

Ari Löytynoja1, Nick Goldman

  • 1EMBL-European Bioinformatics Institute, Hinxton, UK. ari@ebi.ac.uk

Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences
|October 15, 2008
PubMed
Summary
This summary is machine-generated.

This study introduces an advanced alignment method that models evolutionary changes and regional differences in DNA or protein sequences. It improves accuracy by treating insertions and deletions distinctly, offering reliable sequence homology detection.

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Last Updated: Jun 29, 2026

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin
08:57

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Published on: August 14, 2018

Creating and Applying a Reference to Facilitate the Discussion and Classification of Proteins in a Diverse Group
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Published on: August 16, 2017

A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq
07:09

A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq

Published on: May 28, 2021

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Evolutionary Biology

Background:

  • Traditional sequence alignment methods can introduce systematic errors by not adequately distinguishing evolutionary events like insertions and deletions.
  • Understanding regional heterogeneity in evolutionary processes is crucial for accurate sequence analysis.

Purpose of the Study:

  • To extend a phylogeny-aware progressive alignment method to simultaneously model regional heterogeneity and evolution.
  • To develop a flexible, probabilistic approach for aligning nucleotide and amino acid sequences with varying evolutionary rates.

Main Methods:

  • Developed a novel, phylogeny-aware progressive alignment method.
  • Integrated simultaneous modeling of regional heterogeneity and evolutionary processes.
  • Employed a fully probabilistic framework for evolutionary modeling.

Main Results:

  • The method accurately recognizes insertions and deletions as distinct evolutionary events, avoiding traditional alignment errors.
  • Provides estimates of regional evolutionary process heterogeneity and local solution reliability.
  • Allows adjustment of alignment sensitivity and specificity, including leaving highly divergent sequences unaligned.

Conclusions:

  • The enhanced alignment method offers a more accurate and reliable approach for analyzing sequences with complex evolutionary patterns.
  • This probabilistic model is adaptable to various sequence types and evolutionary scenarios, improving homology detection.
  • The ability to control specificity enhances the meaningful detection of homology in divergent sequences.