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

Conservation of Protein Domains Over Different Proteins02:26

Conservation of Protein Domains Over Different Proteins

10.8K
Protein domains are small structurally independent units that are part of a single amino acid chain.  Although these domains are often structurally independent, they may rely on synergistic effects to perform their functions as part of a larger protein. Protein domains may be conserved within the same organism, as well as across different organisms.
A limited set of protein domains often duplicate and recombine during evolution. These domains can be organized in different combinations to...
10.8K
Membrane Domains01:18

Membrane Domains

5.4K
The membrane domains concentrate specific lipids and proteins at one place within the membrane, which helps in cell signaling, adhesion, and other critical cellular processes. These domains can differ in size, composition, function, and lifespan.
Protein Domains
The membrane comprises a group of distinct proteins responsible for carrying out a cell's specific function. For example, the plasma membrane of the human sperm, or a single germ cell, contains a unique set of proteins in the...
5.4K
Conservation of Protein Domains02:26

Conservation of Protein Domains

3.1K
3.1K
Neural Circuits01:25

Neural Circuits

1.2K
Neural circuits and neuronal pools are two of the main structures found in the nervous system. Neural circuits are networks of neurons that work together to carry out a specific task or process. They consist of interconnected neurons and glial cells, which provide structural and metabolic support.
Neuronal pools are collections of nerve cells with similar functions and interact through chemical and electrical signals. These pools include both interneurons (the central neural circuit nodes that...
1.2K
Mechanisms of Membrane Domain Formation00:59

Mechanisms of Membrane Domain Formation

3.0K
Different physical properties of lipids and proteins allow them to localize and form distinct islands or domains in the membrane. Some membrane domains are formed due to protein-protein interactions, whereas others are formed due to the presence of specific lipids such as sphingolipids and sterols—for example, large proteins, such as bacteriorhodopsin, aggregate and create distinct domains.
Another mechanism for membrane domain formation involves membrane proteins interacting with...
3.0K
Multi-pass Transmembrane Proteins and β-barrels01:09

Multi-pass Transmembrane Proteins and β-barrels

5.3K
In multi-pass transmembrane proteins, the polypeptide chain crosses the membrane more than once. The transmembrane polypeptide chain either forms an α-helix or β-strand structure. α-Helix containing multi-pass transmembrane proteins are ubiquitous, whereas β-strand containing ones are mainly found in gram-negative bacteria, mitochondria, and chloroplasts.
α-Helix containing multi-pass transmembrane proteins
Multi-pass transmembrane proteins such as...
5.3K

You might also read

Related Articles

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

Sort by
Same author

TEDLH: Domain HMMs for sensitive detection of remote homologues.

Bioinformatics (Oxford, England)·2026
Same author

On the state of protein function prediction: a report on the fourth CAFA challenge.

bioRxiv : the preprint server for biology·2026
Same author

Mind the gap: the challenges and opportunities for genomics-driven harnessing of plant metabolic diversity for therapeutic applications.

Current opinion in biotechnology·2026
Same author

Leveraging protein language models and a scoring function for indel characterization and transfer learning.

Patterns (New York, N.Y.)·2026
Same author

CACHE Challenge #3: Targeting the Nsp3 Macrodomain of SARS-CoV-2.

Journal of chemical information and modeling·2026
Same author

AlphaFold Protein Structure Database 2025: a redesigned interface and updated structural coverage.

Nucleic acids research·2025

Related Experiment Video

Updated: Jun 26, 2025

Deep Learning-Based Segmentation of Cryo-Electron Tomograms
10:25

Deep Learning-Based Segmentation of Cryo-Electron Tomograms

Published on: November 11, 2022

8.7K

Chainsaw: protein domain segmentation with fully convolutional neural networks.

Jude Wells1, Alex Hawkins-Hooker1, Nicola Bordin2

  • 1Centre for Artificial Intelligence, University College London, WC1E 6BT, United Kingdom.

Bioinformatics (Oxford, England)
|May 8, 2024
PubMed
Summary

Chainsaw, a new supervised learning method, accurately identifies protein domains, surpassing existing tools. This advance aids in understanding protein structure, function, and evolution using predicted protein models.

More Related Videos

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
03:31

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

522
Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
04:48

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

2.7K

Related Experiment Videos

Last Updated: Jun 26, 2025

Deep Learning-Based Segmentation of Cryo-Electron Tomograms
10:25

Deep Learning-Based Segmentation of Cryo-Electron Tomograms

Published on: November 11, 2022

8.7K
Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
03:31

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

522
Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
04:48

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

2.7K

Area of Science:

  • Structural biology
  • Bioinformatics
  • Computational biology

Background:

  • Protein domains are essential for protein structure, function, evolution, and design.
  • Accurate protein structure prediction generates vast datasets, necessitating effective domain partitioning for evolutionary and functional analysis.

Purpose of the Study:

  • To introduce Chainsaw, a novel supervised learning approach for protein domain parsing.
  • To demonstrate that Chainsaw outperforms current state-of-the-art methods in domain prediction accuracy.

Main Methods:

  • Chainsaw employs a fully convolutional neural network to predict residue co-membership probabilities within domains.
  • Domain assignments are determined by an algorithm optimizing residue-to-domain mapping based on pairwise probabilities.
  • The method was evaluated against established domain annotations and human expert preferences on predicted structures.

Main Results:

  • Chainsaw achieves 78% accuracy in matching CATH domain annotations, exceeding the 72% accuracy of the next best method.
  • Human evaluators showed a twofold preference for Chainsaw's domain predictions on AlphaFold models compared to alternative approaches.
  • The study highlights the effectiveness of supervised learning for accurate protein domain parsing.

Conclusions:

  • Chainsaw represents a significant advancement in automated protein domain parsing.
  • Its superior performance enhances the utility of predicted protein structures for biological research.
  • The tool is available for use in advancing protein structure and function studies.