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

Heterochromatin02:38

Heterochromatin

14.0K
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...
14.0K
Chromatin Modification in iPS Cells01:32

Chromatin Modification in iPS Cells

1.7K
Chromatin modification alters gene expression; therefore, scientists can add histone-modifying enzymes, histone variants, and chromatin remodeling complexes to somatic cells to aid reprogramming into pluripotent stem (iPS) cells.
Compact chromatin makes reprogramming difficult. Enzymes, such as histone demethylases and acetyltransferases, are often added during reprogramming to loosen the chromatin, making the DNA more accessible to transcription factors. Molecules that inhibit histone...
1.7K
Chromatin Immunoprecipitation- ChIP02:36

Chromatin Immunoprecipitation- ChIP

11.2K
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...
11.2K

You might also read

Related Articles

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

Sort by
Same author

Machine Learning Identification of Cell-Type-Specific Molecular Signatures Distinguishing COVID-19 from Other Lower Respiratory Tract Diseases.

Life (Basel, Switzerland)·2026
Same author

Machine Learning-Based Identification of Candidate Serum miRNA Features for Pan-Cancer and Cancer Type Classification.

Life (Basel, Switzerland)·2026
Same author

Association between gut microbiota and imaging biomarkers in arteriosclerotic cerebral small vessel disease with idiopathic normal pressure hydrocephalus.

Frontiers in neuroscience·2026
Same author

SIM: Discovery of novel RNA-targeting argonautes by self-iterative learning from scarce data.

Acta pharmaceutica Sinica. B·2026
Same author

Identification of Gene Signatures Differentiating Cancer from Normal Tissues Across Histological Classifications of Gastric Adenocarcinoma via Machine Learning Methods.

Biochemical genetics·2026
Same author

Retraction Note: Testing how financial development led to energy efficiency? Environmental consideration as a mediating concern.

Environmental science and pollution research international·2026

Related Experiment Video

Updated: Aug 6, 2025

Single-Cell Factor Localization on Chromatin using Ultra-Low Input Cleavage Under Targets and Release using Nuclease
09:20

Single-Cell Factor Localization on Chromatin using Ultra-Low Input Cleavage Under Targets and Release using Nuclease

Published on: February 1, 2022

2.8K

Characterization of chromatin accessibility patterns in different mouse cell types using machine learning methods at

Yaochen Xu1, FeiMing Huang2, Wei Guo3

  • 1Department of Mathematics, School of Sciences, Shanghai University, Shanghai, China.

Frontiers in Genetics
|March 20, 2023
PubMed
Summary
This summary is machine-generated.

This study identifies key genes and epigenetic patterns distinguishing cell types using single-cell chromatin accessibility data. Findings advance understanding of cell function and classification through novel marker genes.

Keywords:
biomarker geneschromatin accessibilitychromatin heterogeneitymachine learningmouse cell typesingle-cell resolution

More Related Videos

Mapping Genome-wide Accessible Chromatin in Primary Human T Lymphocytes by ATAC-Seq
09:08

Mapping Genome-wide Accessible Chromatin in Primary Human T Lymphocytes by ATAC-Seq

Published on: November 13, 2017

18.1K
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

4.9K

Related Experiment Videos

Last Updated: Aug 6, 2025

Single-Cell Factor Localization on Chromatin using Ultra-Low Input Cleavage Under Targets and Release using Nuclease
09:20

Single-Cell Factor Localization on Chromatin using Ultra-Low Input Cleavage Under Targets and Release using Nuclease

Published on: February 1, 2022

2.8K
Mapping Genome-wide Accessible Chromatin in Primary Human T Lymphocytes by ATAC-Seq
09:08

Mapping Genome-wide Accessible Chromatin in Primary Human T Lymphocytes by ATAC-Seq

Published on: November 13, 2017

18.1K
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

4.9K

Area of Science:

  • Genomics
  • Epigenetics
  • Cell Biology

Background:

  • Chromatin accessibility, a measure of genome compaction, varies across cell types.
  • Identifying cell-specific markers is crucial for understanding cell function and classification.
  • Single-cell resolution reveals chromatin heterogeneity.

Purpose of the Study:

  • To identify transcriptionally active chromosome segments and associated genes at single-cell resolution.
  • To develop an efficient classifier for distinguishing cell types based on chromatin accessibility.
  • To discover novel marker genes and epigenetic patterns unique to specific cell types.

Main Methods:

  • Single-cell combinatorial indexing assay for ATAC-seq (sci-ATAC-seq) on 69,015 cells from 77 cell types.
  • Boruta and Incremental Feature Selection (IFS) for gene selection and Random Forest (RF) classifier development.
  • Autoencoder and Light Gradient Boosting Machine for optimizing the RF classifier performance.

Main Results:

  • Analysis of 436,206 active chromosome segments identified 3897 important genes.
  • An optimized RF classifier achieved a Matthews Correlation Coefficient (MCC) of 0.838.
  • Identified marker genes like H2-Dmb2 (antigen-presenting cells) and Tenm2 (T cells).

Conclusions:

  • Chromatin accessibility data can effectively distinguish cell types at single-cell resolution.
  • Novel marker genes and unique epigenetic patterns were identified for various cell types.
  • This work enhances the understanding of chromatin accessibility's role in cell-specific functions and classification.