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

Conserved Binding Sites01:49

Conserved Binding Sites

4.3K
Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
Binding sites are often located in large pockets, and if their location on a protein’s surface is unknown, it can be predicted using various approaches. The energetic method computationally...
4.3K

You might also read

Related Articles

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

Sort by
Same author

Enhancement of ferroptosis in escape variant tumor cells by IFN-γ derived from antigen-specific T cells controls tumor with heterogeneity.

Cancer immunology research·2026
Same author

Primary Squamous Cell Carcinoma of the Pancreas and Duodenum.

Digestive diseases and sciences·2026
Same author

Natural Small Molecules Targeting Oxidative Stress and Redox Homeostasis in Aging: Mechanisms and Therapeutic Potential.

Antioxidants (Basel, Switzerland)·2026
Same author

Transport of functionalized nanoplastics in goethite-coated saturated porous media: Synergistic effect of polyacrylamide coupled with solution chemistry.

Journal of hazardous materials·2026
Same author

Chronic ammonia-N exposure impairs the intestinal health of the Siberian sturgeon (Acipenser baerii Brandt): through the pathways of oxidative stress, tight junction proteins, inflammatory factors, and intestinal microbiota.

Fish & shellfish immunology·2026
Same author

C-terminus-outward orientation of SARS-CoV-2 envelope proteins on viral capsid enables a novel virus-cell interaction pathway.

Frontiers in cellular and infection microbiology·2026

Related Experiment Video

Updated: Aug 2, 2025

HOX Loci Focused CRISPR/sgRNA Library Screening Identifying Critical CTCF Boundaries
10:10

HOX Loci Focused CRISPR/sgRNA Library Screening Identifying Critical CTCF Boundaries

Published on: March 31, 2019

8.4K

Prediction of CTCF loop anchor based on machine learning.

Xiao Zhang1,2,3, Wen Zhu1,3, Huimin Sun4

  • 1School of Mathematics and Statistics, Hainan Normal University, Haikou, China.

Frontiers in Genetics
|April 20, 2023
PubMed
Summary

Researchers developed a machine learning model to predict CTCF-mediated chromatin loop anchors. The model, achieving 0.8646 accuracy, identifies that CTCF binding strength and pattern determine anchor selection.

Keywords:
3D GenomeCTCFChromatin LoopDNA sequenceMachine Learning

More Related Videos

Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model
07:13

Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model

Published on: April 18, 2025

158
Associated Chromosome Trap for Identifying Long-range DNA Interactions
14:49

Associated Chromosome Trap for Identifying Long-range DNA Interactions

Published on: April 23, 2011

14.5K

Related Experiment Videos

Last Updated: Aug 2, 2025

HOX Loci Focused CRISPR/sgRNA Library Screening Identifying Critical CTCF Boundaries
10:10

HOX Loci Focused CRISPR/sgRNA Library Screening Identifying Critical CTCF Boundaries

Published on: March 31, 2019

8.4K
Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model
07:13

Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model

Published on: April 18, 2025

158
Associated Chromosome Trap for Identifying Long-range DNA Interactions
14:49

Associated Chromosome Trap for Identifying Long-range DNA Interactions

Published on: April 23, 2011

14.5K

Area of Science:

  • Genomics
  • Molecular Biology
  • Bioinformatics

Background:

  • Cellular activities are influenced by 3D genome structure.
  • Insulators, like CTCF, organize higher-order structures and form chromatin loop barriers.
  • CTCF has numerous genome-wide binding sites, but only some act as chromatin loop anchors, with selection mechanisms unclear.

Purpose of the Study:

  • To investigate sequence preferences and binding strengths of anchor vs. non-anchor CTCF sites.
  • To develop a machine learning model for predicting CTCF sites that form chromatin loop anchors.

Main Methods:

  • Comparative analysis of CTCF binding sites (anchor vs. non-anchor).
  • Development of a machine learning model utilizing CTCF binding intensity and DNA sequence data.

Main Results:

  • A machine learning model accurately predicted CTCF-mediated chromatin loop anchors with 0.8646 accuracy.
  • CTCF binding strength and binding patterns (zinc finger interactions) are key factors in loop anchor formation.

Conclusions:

  • CTCF core motif and flanking sequences influence binding specificity.
  • This study enhances understanding of chromatin loop anchor selection and aids in predicting CTCF-mediated loops.