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

Protein Networks02:26

Protein Networks

4.7K
An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
4.7K
Protein Networks02:26

Protein Networks

2.9K
2.9K
Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

7.2K
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...
7.2K
RNA Editing02:23

RNA Editing

10.1K
RNA editing is a post-transcriptional modification where a precursor mRNA (pre-mRNA) nucleotide sequence is changed by base insertion, deletion, or modification. The extent of RNA editing varies from a few hundred bases, in mitochondrial DNA of trypanosomes, to a just single base, in nuclear genes of mammals. Even a single base change in the pre-mRNA can convert a codon for one amino acid into the codon for another amino acid or a stop codon. This type of re-coding can significantly affect the...
10.1K
Protein-protein Interfaces02:04

Protein-protein Interfaces

15.0K
Many proteins form complexes to carry out their functions, making protein-protein interactions (PPIs) essential for an organism's survival. Most PPIs are stabilized by numerous weak noncovalent chemical forces. The physical shape of the interfaces determines the way two proteins interact. Many globular proteins have closely-matching shapes on their surfaces, which form a large number of weak bonds. Additionally, many PPIs occur between two helices or between a surface cleft and a...
15.0K
Types of Genetic Transfer Between Organisms02:18

Types of Genetic Transfer Between Organisms

31.6K
Genetic transfer occurs when genetic information is passed from one organism to another. It occurs via two mechanisms: vertical gene transfer and horizontal gene transfer. Vertical gene transfer occurs when genetic information is transferred from one generation to the next, which happens much more frequently than horizontal gene transfer. Both sexual and asexual reproduction are forms of vertical gene transfer, where one or more organisms pass some or all of their genome onto their progeny.
31.6K

You might also read

Related Articles

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

Sort by
Same author

Shape-constrained, changepoint additive models for time series omics data with cpam.

Nucleic acids research·2026
Same author

Leveraging advances in machine learning for the robust classification and interpretation of networks.

Royal Society open science·2025
Same author

Dehydration rapidly induces expression of NCED genes from a single subclade in diverse eudicots.

Planta·2025
Same author

Spectral cluster supertree: fast and statistically robust merging of rooted phylogenetic trees.

Frontiers in molecular biosciences·2024
Same author

David Penny-An indomitable evolutionary biologist.

Proceedings of the National Academy of Sciences of the United States of America·2024
Same author

Ancient and Modern Genomes Reveal Microsatellites Maintain a Dynamic Equilibrium Through Deep Time.

Genome biology and evolution·2024
Same journal

GMSA: A Graph Matching and Point Cloud Registration-Based Method for Spatial Transcriptomics Data Alignment.

Journal of computational biology : a journal of computational molecular cell biology·2026
Same journal

Investigations on Multiple Protein Scaffold Filling.

Journal of computational biology : a journal of computational molecular cell biology·2026
Same journal

Cell Type Prediction for Single-Cell RNA Sequencing Utilizing Unsupervised Domain Adaptation and Semi-Supervised Learning.

Journal of computational biology : a journal of computational molecular cell biology·2026
Same journal

PPIGAN: Prediction of Protein-Protein Interactions Using Generative Adversarial Networks.

Journal of computational biology : a journal of computational molecular cell biology·2026
Same journal

Deep Structure-Enhanced Cell Clustering Model for Single-Cell RNA Sequencing Data.

Journal of computational biology : a journal of computational molecular cell biology·2026
Same journal

Asymmetric Drug-Drug Interaction Prediction Based on Generative Adversarial Networks and Knowledge Graph.

Journal of computational biology : a journal of computational molecular cell biology·2026
See all related articles

Related Experiment Video

Updated: Mar 19, 2026

Divergence of Root Microbiota in Different Habitats based on Weighted Correlation Networks
09:49

Divergence of Root Microbiota in Different Habitats based on Weighted Correlation Networks

Published on: September 25, 2021

4.9K

Biological Network Edit Distance.

Martin McGrane1, Michael A Charleston2

  • 11 School of Information Technologies, The University of Sydney , Sydney, New South Wales, Australia .

Journal of Computational Biology : a Journal of Computational Molecular Cell Biology
|June 17, 2016
PubMed
Summary
This summary is machine-generated.

We developed a new method to measure the distance between biological networks, revealing their evolutionary history. This approach accurately identifies evolutionary changes and reconstructs evolutionary trees for gene regulatory networks.

Keywords:
and networksgene networksgenetic algorithmsgraphs

More Related Videos

Modeling the Functional Network for Spatial Navigation in the Human Brain
05:55

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

1.6K
Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays
14:06

Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays

Published on: November 12, 2012

47.1K

Related Experiment Videos

Last Updated: Mar 19, 2026

Divergence of Root Microbiota in Different Habitats based on Weighted Correlation Networks
09:49

Divergence of Root Microbiota in Different Habitats based on Weighted Correlation Networks

Published on: September 25, 2021

4.9K
Modeling the Functional Network for Spatial Navigation in the Human Brain
05:55

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

1.6K
Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays
14:06

Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays

Published on: November 12, 2012

47.1K

Area of Science:

  • Systems Biology
  • Computational Biology
  • Evolutionary Biology

Background:

  • Biological network evolution is complex and not fully understood.
  • Existing methods for analyzing biological networks often overlook interaction information.
  • Measuring distances between biological networks with unknown evolutionary histories is challenging.

Purpose of the Study:

  • To present a novel model for calculating biological network distance.
  • To demonstrate the model's implementation using simulated gene regulatory networks.
  • To compare the new method with existing network alignment techniques.

Main Methods:

  • Developed a new biological network distance metric.
  • Implemented the metric using simulated gene regulatory networks.
  • Compared the proposed method against established network alignment algorithms.

Main Results:

  • The proposed network distance model effectively identifies evolutionary changes in biological networks.
  • The method significantly outperforms existing approaches in network alignment.
  • Successfully recovered evolutionary trees describing relationships between simulated networks.

Conclusions:

  • Network distance metrics provide valuable insights into biological network evolution.
  • The presented model offers a powerful tool for understanding the history of biological networks.
  • This work advances the study of biological network evolution and comparative network analysis.