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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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Updated: Jun 6, 2026

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin
08:57

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Published on: August 14, 2018

Co-evolution is incompatible with the Markov assumption in phylogenetics.

Tamir Tuller1, Elchanan Mossel

  • 1Faculty of Mathematics and Computer Science, Weizmann Institute of Science, PO Box 26, Rehovot 76100, Israel. tamirtul@post.tau.ac.il

IEEE/ACM Transactions on Computational Biology and Bioinformatics
|December 1, 2010
PubMed
Summary

Markov models are widely used in molecular evolution. This study shows that extreme protein co-evolution can violate the Markov assumption, suggesting a need for new probabilistic models.

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Following the Dynamics of Structural Variants in Experimentally Evolved Populations
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Area of Science:

  • Evolutionary biology
  • Computational biology
  • Bioinformatics

Background:

  • Markov models are standard tools for analyzing molecular evolution.
  • Recent research posits that interacting proteins co-evolve.
  • Understanding co-evolutionary dynamics is crucial for functional inference.

Purpose of the Study:

  • To investigate whether the Markov assumption holds for co-evolving protein families.
  • To assess the impact of strong co-evolution on evolutionary models.
  • To identify limitations of current models in specific evolutionary scenarios.

Main Methods:

  • Analysis of hundreds of orthologous protein sets across three fungal species.
  • Application of co-evolutionary relation analysis.
  • Evaluation of adherence to the Markov assumption in observed evolutionary patterns.

Main Results:

  • Demonstrated that co-evolutionary relationships can violate the Markov assumption.
  • Identified specific cases where the Markov assumption is compromised.
  • Highlighted the potential for significant deviations in highly co-evolved systems.

Conclusions:

  • The standard Markov assumption may not be universally applicable in molecular evolution, especially with strong co-evolution.
  • There is a need to develop and explore alternative probabilistic models.
  • Future models should account for complex co-evolutionary dependencies to improve accuracy.