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

Chromatin Immunoprecipitation- ChIP02:36

Chromatin Immunoprecipitation- ChIP

12.9K
Chromatin immunoprecipitation, or ChIP, is an antibody-based technique used to identify sites on DNA that bind to transcription factors of interest or histone proteins. It also helps determine the type of histone modifications such as acetylation, phosphorylation, or methylation.
Types of ChIP
ChIP can be divided into two types - X-ChIP and N-ChIP. X-ChIP involves in vivo cross-linking of histones and regulatory proteins to DNA, fragmenting the DNA by sonication, and isolating the protein-DNA...
12.9K
Chromatin Position Affects Gene Expression02:35

Chromatin Position Affects Gene Expression

25.3K
Chromatin is the massive complex of DNA and proteins packaged inside the nucleus. The complexity of chromatin folding and how it is packaged inside the nucleus greatly influences  access to genetic information. Generally, the nucleus' periphery is considered transcriptionally repressive, while the cell's interior is considered a transcriptionally active area. 
Topologically Associated Domains (TADs)
The 3-dimensional positioning of chromatin in the nucleus influences the...
25.3K
Heterochromatin02:38

Heterochromatin

19.1K
The extent of chromatin compaction can be studied by staining chromatin using specific DNA binding dyes. Under the microscope, the dense-compacted regions that take up more dye are called heterochromatin. Heterochromatin is further classified into two forms – constitutive heterochromatin and facultative heterochromatin.
Constitutive heterochromatin: It is a highly compact region of chromatin that is mostly concentrated in the centromere and telomere. Unlike euchromatin, the amino acid at...
19.1K

You might also read

Related Articles

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

Sort by
Same author

SHIELD: A weakly supervised graph attention neural network for decoding disease-relevant cell-cell interactions.

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

Brain Connectivity and Machine Learning Approaches to assess the underlying neurobiology and prediction accuracy of anorexia nervosa: A replication study.

Psychiatry research. Neuroimaging·2026
Same author

Human microglial transitions at the Aβ-tau inflection point associate with divergent pathways to dementia and resilience.

Nature medicine·2026
Same author

Assessing the de novo paradigm in sporadic early-onset Alzheimer disease trios.

Molecular psychiatry·2026
Same author

Host-microbial interactions at the nasal mucosa in young children and adults: A retrospective, cross-sectional study.

Cell reports·2026
Same author

Attrition and representativeness in development and validation of online symptom checkers-a case study on the <i>Rheumatic</i>? Questionnaire.

Frontiers in artificial intelligence·2026

Related Experiment Video

Updated: Apr 12, 2026

High-Resolution Mapping of Protein-DNA Interactions in Mouse Stem Cell-Derived Neurons using Chromatin Immunoprecipitation-Exonuclease ChIP-Exo
08:40

High-Resolution Mapping of Protein-DNA Interactions in Mouse Stem Cell-Derived Neurons using Chromatin Immunoprecipitation-Exonuclease ChIP-Exo

Published on: August 14, 2020

5.4K

Hi-C Chromatin Interaction Networks Predict Co-expression in the Mouse Cortex.

Sepideh Babaei1, Ahmed Mahfouz2, Marc Hulsman3

  • 1Delft Bioinformatics Lab, Delft University of Technology, Delft, The Netherlands.

Plos Computational Biology
|May 13, 2015
PubMed
Summary

Predicting gene co-expression is improved by analyzing the multi-resolution chromatin interaction network. Scale-aware topological measures capture both direct gene interactions and larger chromatin compartments for accurate spatial co-expression prediction.

More Related Videos

Deciphering High-Resolution 3D Chromatin Organization via Capture Hi-C
09:32

Deciphering High-Resolution 3D Chromatin Organization via Capture Hi-C

Published on: October 14, 2022

4.9K
Isolation and Cultivation of Neural Progenitors Followed by Chromatin-Immunoprecipitation of Histone 3 Lysine 79 Dimethylation Mark
10:09

Isolation and Cultivation of Neural Progenitors Followed by Chromatin-Immunoprecipitation of Histone 3 Lysine 79 Dimethylation Mark

Published on: January 26, 2018

8.0K

Related Experiment Videos

Last Updated: Apr 12, 2026

High-Resolution Mapping of Protein-DNA Interactions in Mouse Stem Cell-Derived Neurons using Chromatin Immunoprecipitation-Exonuclease ChIP-Exo
08:40

High-Resolution Mapping of Protein-DNA Interactions in Mouse Stem Cell-Derived Neurons using Chromatin Immunoprecipitation-Exonuclease ChIP-Exo

Published on: August 14, 2020

5.4K
Deciphering High-Resolution 3D Chromatin Organization via Capture Hi-C
09:32

Deciphering High-Resolution 3D Chromatin Organization via Capture Hi-C

Published on: October 14, 2022

4.9K
Isolation and Cultivation of Neural Progenitors Followed by Chromatin-Immunoprecipitation of Histone 3 Lysine 79 Dimethylation Mark
10:09

Isolation and Cultivation of Neural Progenitors Followed by Chromatin-Immunoprecipitation of Histone 3 Lysine 79 Dimethylation Mark

Published on: January 26, 2018

8.0K

Area of Science:

  • Genomics
  • Systems Biology
  • Bioinformatics

Background:

  • The three-dimensional (3D) genome conformation within the cell nucleus is crucial for regulating gene expression.
  • Previous research indicates a significant correlation between chromatin interactions and gene co-expression patterns.
  • Accurately predicting gene co-expression from long-range chromatin interactions remains a complex challenge.

Purpose of the Study:

  • To develop a method for accurately predicting spatial gene co-expression using network topology.
  • To investigate the utility of scale-aware topological measures in characterizing chromatin interaction networks.
  • To assess the impact of multi-resolution network analysis on co-expression prediction accuracy.

Main Methods:

  • Characterization of the cortical chromatin interaction network topology using scale-aware topological measures.
  • Development and application of network analysis techniques to multi-resolution chromatin interaction data.
  • Validation of predictive models for spatial gene co-expression in the mouse cortex.

Main Results:

  • The chromatin interaction profile of gene pairs is a reliable predictor of their spatial co-expression.
  • Employing scale-aware topological measures of the multi-resolution chromatin interaction network significantly enhances prediction accuracy.
  • Accurate prediction of spatial co-expression is achievable by characterizing network topology at various scales.

Conclusions:

  • Scale-aware topological characterization of chromatin interaction networks is essential for improving gene co-expression prediction.
  • Effective co-expression prediction necessitates considering diverse levels of chromatin interactions, from direct gene contacts to larger chromatin compartments.
  • This study highlights the importance of multi-scale network analysis in understanding genome organization and gene regulation.