Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Chromatin Immunoprecipitation- ChIP

Chromatin Immunoprecipitation- ChIP

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...

You might also read

Related Articles

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

Sort by

Same author

Induction of multiple HIV-1 neutralizing B Cell Precursors in Humans.

medRxiv : the preprint server for health sciences·2026

Same author

Comparative characterization of human accelerated regions in neurons.

Nature·2025

Same author

An engineered immunogen activates diverse HIV broadly neutralizing antibody precursors and promotes acquisition of improbable mutations.

Science translational medicine·2025

Same author

Integrative analysis of the 3D genome and epigenome in mouse embryonic tissues.

Nature structural & molecular biology·2024

Same author

Neonatal immunity associated with heterologous HIV-1 neutralizing antibody induction in SHIV-infected Rhesus Macaques.

Nature communications·2024

Same author

Combinatorial transcription factor binding encodes cis-regulatory wiring of mouse forebrain GABAergic neurogenesis.

Developmental cell·2024

Same journal

Interplay between genomic architecture alterations and GDF6 regulation: a candidate mechanism in Nablus mask-like facial syndrome.

HGG advances·2026

Same journal

Pediatric High-Grade Gliomas and Cancer Predisposition Syndromes: A Retrospective Study.

HGG advances·2026

Same journal

Multi-ancestry genome-wide association meta-analysis of hepatocellular carcinoma identifies eight risk loci including MAP3K9, DHRS1, MTTP, and 8q24.21.

HGG advances·2026

Same journal

Expanding the ABCA2-associated neurodevelopmental phenotype.

HGG advances·2026

Same journal

A Pseudotime-Dependent TWAS Framework Identifies Disease Genes along Cell Developmental Paths.

HGG advances·2026

Same journal

A lethal form of ASCC3 disease: severe global developmental delay, axial hypotonia, hypoplasia of corpus callosum, hypothyroidism and micropenis.

HGG advances·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Oct 21, 2025

Associated Chromosome Trap for Identifying Long-range DNA Interactions

Associated Chromosome Trap for Identifying Long-range DNA Interactions

Published on: April 23, 2011

MUNIn: A statistical framework for identifying long-range chromatin interactions from multiple samples.

Weifang Liu^1,2, Yuchen Yang^3,4,5,2, Armen Abnousi⁶

¹Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.

|September 6, 2021

Summary

This summary is machine-generated.

We developed MUNIn, a new tool to find long-range chromatin interactions across multiple samples. It improves accuracy and power for detecting shared and specific interactions, advancing our understanding of genome function and disease.

More Related Videos

Capturing Chromosome Conformation Across Length Scales

Capturing Chromosome Conformation Across Length Scales

Published on: January 20, 2023

Chromatin Interaction Analysis with Paired-End Tag Sequencing ChIA-PET for Mapping Chromatin Interactions and Understanding Transcription Regulation

Chromatin Interaction Analysis with Paired-End Tag Sequencing ChIA-PET for Mapping Chromatin Interactions and Understanding Transcription Regulation

Published on: April 30, 2012

Related Experiment Videos

Last Updated: Oct 21, 2025

Associated Chromosome Trap for Identifying Long-range DNA Interactions

Associated Chromosome Trap for Identifying Long-range DNA Interactions

Published on: April 23, 2011

Capturing Chromosome Conformation Across Length Scales

Capturing Chromosome Conformation Across Length Scales

Published on: January 20, 2023

Chromatin Interaction Analysis with Paired-End Tag Sequencing ChIA-PET for Mapping Chromatin Interactions and Understanding Transcription Regulation

Chromatin Interaction Analysis with Paired-End Tag Sequencing ChIA-PET for Mapping Chromatin Interactions and Understanding Transcription Regulation

Published on: April 30, 2012

Area of Science:

Genomics
Molecular Biology
Bioinformatics

Background:

Chromatin spatial organization, or interactome, is crucial for genome function, transcriptional regulation, and understanding disease.
Identifying long-range chromatin interactions is key to analyzing interactomic data.
Current methods analyze single samples, failing to address multi-sample heterogeneity and sequencing depth variations.

Purpose of the Study:

To develop a novel statistical framework for identifying long-range chromatin interactions from multiple samples.
To address limitations of existing uni-sample analysis tools by incorporating sample heterogeneity.
To provide a unified approach for the integrative analysis of interactomic data.

Main Methods:

Developed MUNIn (multiple-sample unifying long-range chromatin-interaction detector), a novel statistical framework.
Utilized a hierarchical hidden Markov random field (H-HMRF) model.
Incorporated dependencies between neighboring loci pairs and across multiple samples within the H-HMRF model.

Main Results:

MUNIn achieved significantly lower false-positive rates (33.1%-36.2%) for sample-specific interactions.
Demonstrated substantially enhanced statistical power (up to 74.3%) for detecting shared chromatin interactions.
Outperformed uni-sample analysis methods in comprehensive simulation and real data analyses.

Conclusions:

MUNIn offers a robust and statistically sound framework for the integrative analysis of multi-sample interactomic data.
The tool enhances the detection of both shared and sample-specific long-range chromatin interactions.
MUNIn is a valuable addition to the bioinformatics toolkit for studying genome organization and function across diverse biological contexts.