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

FluNexus: A versatile web platform for antigenic prediction and visualization of influenza A viruses.

iMeta·2026

Same author

Mosaic integration of spatial multi-omics with SpaMosaic.

Nature genetics·2026

Same author

Artificial Intelligence Powers Protein Functional Annotation.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2026

Same author

NanoLoop: A Deep Learning Framework Leveraging Nanopore Sequencing for Chromatin Loop Prediction.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2026

Same author

scHLens: a web server for hierarchically and interactively exploring single cell RNA-seq data.

Briefings in bioinformatics·2025

Same author

Subgraph Neural Networks Enhanced by Global Similarity for Drug Repositioning.

Interdisciplinary sciences, computational life sciences·2025

Same journal

Somatic mobility of transposons is explosive and shaped by distinct integration biases in Arabidopsis thaliana.

Genome biology·2026

Same journal

UK Biobank whole-genome sequencing reveals robust contributions of rare variants to complex-trait heritability.

Genome biology·2026

Same journal

A one-week automated genome-wide optical pooled screen using OttoSeq.

Genome biology·2026

Same journal

Integrated lipidomic and transcriptomic profiling of the host response in human malaria.

Genome biology·2026

Same journal

Centromeric satellite expansion drives genome evolution in the snowy owl.

Genome biology·2026

Same journal

Mapping the landscape of allele-specific expression in porcine genomes.

Genome biology·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Oct 5, 2025

An Integrated Platform for Genome-wide Mapping of Chromatin States Using High-throughput ChIP-sequencing in Tumor Tissues

An Integrated Platform for Genome-wide Mapping of Chromatin States Using High-throughput ChIP-sequencing in Tumor Tissues

Published on: April 5, 2018

Bacon: a comprehensive computational benchmarking framework for evaluating targeted chromatin conformation

Li Tang¹, Matthew C Hill^2,3, Patrick T Ellinor^2,3

¹Hunan Provincial Key Lab on Bioinformatics, School of Computer Science and Engineering, Central South University, Changsha, 410083, China.

|January 22, 2022

Summary

This summary is machine-generated.

This study introduces Bacon, a benchmark framework for evaluating computational methods used in analyzing chromatin conformation capture (3C) data. It provides recommendations for improving HiChIP and ChIA-PET analyses.

Keywords:

Benchmark ChIA-PET Chromatin topology HiChIP Looping

More Related Videos

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

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

Published on: October 14, 2022

Adaptation of Hybridization Capture of Chromatin-associated Proteins for Proteomics to Mammalian Cells

Adaptation of Hybridization Capture of Chromatin-associated Proteins for Proteomics to Mammalian Cells

Published on: June 1, 2018

Related Experiment Videos

Last Updated: Oct 5, 2025

An Integrated Platform for Genome-wide Mapping of Chromatin States Using High-throughput ChIP-sequencing in Tumor Tissues

An Integrated Platform for Genome-wide Mapping of Chromatin States Using High-throughput ChIP-sequencing in Tumor Tissues

Published on: April 5, 2018

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

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

Published on: October 14, 2022

Adaptation of Hybridization Capture of Chromatin-associated Proteins for Proteomics to Mammalian Cells

Adaptation of Hybridization Capture of Chromatin-associated Proteins for Proteomics to Mammalian Cells

Published on: June 1, 2018

Area of Science:

Genomics
Bioinformatics
Molecular Biology

Background:

Chromatin conformation capture (3C) technologies detect topological genomic interactions.
Combining 3C with ChIP (Chromatin Immunoprecipitation) enables identification of long-range genomic interactions.
Analyzing large and complex 3C-based datasets (like HiChIP and ChIA-PET) requires robust computational methods.

Purpose of the Study:

To comprehensively benchmark computational methods for analyzing 3C-based genomic interaction data.
To identify areas for improvement in existing algorithms and processing pipelines.
To provide practical recommendations for users of HiChIP and ChIA-PET data analysis.

Main Methods:

Development of a comprehensive benchmark framework named Bacon.
Evaluation of the performance of several commonly used computational methods for 3C-based data analysis.
Comparative analysis of algorithms and processing pipelines.

Main Results:

The study presents a systematic evaluation of computational pipelines for 3C-based technologies.
Identified specific algorithms and pipelines that require further development or optimization.
Established a basis for selecting appropriate analytical tools for HiChIP and ChIA-PET data.

Conclusions:

A robust benchmark framework (Bacon) is essential for advancing the analysis of 3C-based genomic interaction data.
Performance evaluation guides the improvement of computational tools for genomics.
Recommendations are provided to enhance the accuracy and efficiency of HiChIP and ChIA-PET analyses.