Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

5.8K
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...
5.8K
Microbial Phylogeny01:28

Microbial Phylogeny

84
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,...
84
Microbial Classification System01:24

Microbial Classification System

1.8K
Classification is the process of organizing organisms into hierarchically inclusive groups based on their phenotypic similarities or evolutionary relationships. A species comprises one or more strains, and closely related species are grouped into genera. Genera are further classified into families, families into orders, orders into classes, and so forth, up to the domain level, which is the broadest taxonomic rank derived from a combination of phenotypic and genotypic data.The nomenclature of...
1.8K
Applications of Molecular Taxonomy01:20

Applications of Molecular Taxonomy

702
Molecular taxonomy has revolutionized the understanding and classification of bacteria, providing precise insights into their diversity, evolutionary relationships, and ecological roles. By utilizing molecular techniques such as DNA sequencing and fingerprinting, researchers have made significant strides in various fields related to bacterial studies.Resolving Taxonomic AmbiguitiesMolecular taxonomy has been instrumental in distinguishing closely related bacterial species initially thought to...
702
Gene Evolution - Fast or Slow?02:05

Gene Evolution - Fast or Slow?

6.2K
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...
6.2K
Gene Evolution - Fast or Slow?02:05

Gene Evolution - Fast or Slow?

2.5K
2.5K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Mechanisms for bump state localization in two-dimensional networks of leaky integrate-and-fire neurons.

Chaos (Woodbury, N.Y.)·2025
Same author

From Turing patterns to chimera states in the 2D Brusselator model.

Chaos (Woodbury, N.Y.)·2023
Same author

Synchronization in Multiplex Leaky Integrate-and-Fire Networks With Nonlocal Interactions.

Frontiers in network physiology·2023
Same author

Controlling the Chimera Form in the Leaky Integrate-and-Fire Model.

Advances in experimental medicine and biology·2022
Same author

Shooting solitaries due to small-world connectivity in leaky integrate-and-fire networks.

Chaos (Woodbury, N.Y.)·2021
Same author

Structural anomalies in brain networks induce dynamical pacemaker effects.

Chaos (Woodbury, N.Y.)·2020
Same journal

Integrative transcriptomics, machine learning, and molecular docking derive a DAM-like macrophage signature for risk stratification and therapeutic nomination in glioblastoma.

Computational biology and chemistry·2026
Same journal

Enhancing robustness in protein function prediction via missing modality imputation and adaptive multimodal fusion.

Computational biology and chemistry·2026
Same journal

Identification of cell pyroptosis-related gene signature for prognosis in skin cutaneous melanoma.

Computational biology and chemistry·2026
Same journal

Short Interrupted Repeats Cassette ensembles of plant nuclear genomes reflect evolutionary route of species.

Computational biology and chemistry·2026
Same journal

M3FusionNet: Cross-cohort multimodal prediction of breast cancer biomarkers.

Computational biology and chemistry·2026
Same journal

Mining negative sequential patterns to improve viral genomic feature representation and classification.

Computational biology and chemistry·2026
See all related articles

Related Experiment Video

Updated: Apr 24, 2026

A Concoction Pipeline for Generating Molecular Operational Taxonomic Units (MOTUs) Among Riparian and Aquatic Beetles
10:23

A Concoction Pipeline for Generating Molecular Operational Taxonomic Units (MOTUs) Among Riparian and Aquatic Beetles

Published on: July 11, 2025

711

Complexity measures for the evolutionary categorization of organisms.

A Provata1, C Nicolis2, G Nicolis3

  • 1Institute of Nanoscience and Nanotechnology, National Center for Scientific Research "Demokritos", 15310 Athens, Greece.

Computational Biology and Chemistry
|September 14, 2014
PubMed
Summary
This summary is machine-generated.

Genomic complexity analysis reveals distinct eukaryotic and prokaryotic DNA signatures. These findings highlight differences in sequence organization and evolutionary patterns, offering new markers for DNA classification.

Keywords:
Block entropyGenomic sequencesIrreversiblyProbability fluxes

More Related Videos

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin
08:57

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Published on: August 14, 2018

14.3K
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

2.1K

Related Experiment Videos

Last Updated: Apr 24, 2026

A Concoction Pipeline for Generating Molecular Operational Taxonomic Units (MOTUs) Among Riparian and Aquatic Beetles
10:23

A Concoction Pipeline for Generating Molecular Operational Taxonomic Units (MOTUs) Among Riparian and Aquatic Beetles

Published on: July 11, 2025

711
Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin
08:57

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Published on: August 14, 2018

14.3K
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

2.1K

Area of Science:

  • Genomics and Bioinformatics
  • Computational Biology
  • Evolutionary Biology

Background:

  • Genomic complexity measures are crucial for understanding DNA sequence characteristics across diverse life forms.
  • Previous studies have explored genomic alphabets, but a comprehensive comparison of statistical and spatial properties across major evolutionary classes is lacking.

Purpose of the Study:

  • To compare genomic characteristics of eukaryotes and bacteria using different alphabetic representations of DNA sequences.
  • To identify reliable markers for discriminating between eukaryotic and prokaryotic DNA based on complexity measures.

Main Methods:

  • Analysis of conditional probability matrices, spatial asymmetry, block entropy, excess entropy, and exit distance distributions.
  • Utilized full four-letter (A, G, C, T) and reduced two-letter (AG-CT, AT-CG) alphabets for sequence comparisons.
  • Examined genomic data from five distinct organisms representing higher eukaryotes, amoebae, unicellular eukaryotes, and bacteria.

Main Results:

  • Eukaryotic genomes exhibit asymmetric conditional probability matrices and long-range characteristics in exit distance distributions, unlike nearly symmetric bacterial genomes with short-range properties.
  • The human genome better accommodates longer block configurations, indicating higher complexity.
  • The AT-CG alphabet reduction accentuates CpG-related properties but masks sequence asymmetry and irreversibility more than the AG-CT alphabet.

Conclusions:

  • Conditional probability, fluxes, block entropy, and exit distance distributions serve as effective markers for distinguishing eukaryotic from prokaryotic DNA.
  • The reduction of the DNA alphabet to two letters masks significant statistical and spatial properties, with AT-CG offering better discrimination than AG-CT.
  • These complexity measures can reveal finer class-related details within eukaryotic and prokaryotic genomes.