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...

Transcription Factors

Transcription Factors

Tissue-specific transcription factors contribute to diverse cellular functions in mammals. For example, the gene for beta globin, a major component of hemoglobin, is present in all cells of the body. However, it is only expressed in red blood cells because the transcription factors that can bind to the promoter sequences of the beta globin gene are only expressed in these cells. Tissue-specific transcription factors also ensure that mutations in these factors may impair only the function of...

Combinatorial Gene Control

Combinatorial Gene Control

Combinatorial gene control is the synergistic action of several transcriptional factors to regulate the expression of a single gene. The absence of one or more of these factors may lead to a significant difference in the level of gene expression or repression.
The expression of more than 30,000 genes is controlled by approximately 2000-3000 transcription factors. This is possible because a single transcription factor can recognize more than one regulatory sequence. The specificity in gene...

You might also read

Related Articles

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

Sort by

Same author

Neural stem cell epigenomes and fate bias are temporally coordinated during mouse cortical development.

Genes & development·2026

Same author

A spatial atlas of human gastrointestinal acute GVHD reveals epithelial and immune dynamics underlying disease pathophysiology.

Science translational medicine·2025

Same author

The Biodiversity Cell Atlas: mapping the tree of life at cellular resolution.

Nature·2025

Same author

A reference model of circulating hematopoietic stem cells across the lifespan with applications to diagnostics.

Nature medicine·2025

Same author

Temporal BMP4 effects on mouse embryonic and extraembryonic development.

Nature·2024

Same author

Modeling T cell temporal response to cancer immunotherapy rationalizes development of combinatorial treatment protocols.

Nature cancer·2024

Same journal

Demonstration of a quantum C-NOT gate in a time-multiplexed fully reconfigurable photonic processor.

Nature communications·2026

Same journal

Nonlinear quantum light source with van der Waals ferroelectric NbOX<sub>2</sub> (X = Br, I).

Nature communications·2026

Same journal

Antagonistic histone H2A variants and autonomous heterochromatin formation shape epigenomic patterns in Arabidopsis.

Nature communications·2026

Same journal

The long tail of nitrate pollution in groundwater challenges governance of global water quality.

Nature communications·2026

Same journal

Select microbial metabolites promote tau aggregation in a murine tauopathy model.

Nature communications·2026

Same journal

Warming climate has lengthened global intense tropical cyclone seasons.

Nature communications·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Jan 15, 2026

Formaldehyde-assisted Isolation of Regulatory Elements to Measure Chromatin Accessibility in Mammalian Cells

Formaldehyde-assisted Isolation of Regulatory Elements to Measure Chromatin Accessibility in Mammalian Cells

Published on: April 2, 2018

IceQream: Quantitative chromosome accessibility analysis using physical TF models.

Akhiad Bercovich^1,2, Aviezer Lifshitz^1,2, Michal Eldar^1,2

¹Weizmann Institute of Science, Department of Computer Science and Applied Mathematics, Rehovot, Israel.

Nature Communications

|October 9, 2025

Summary

This summary is machine-generated.

We developed IceQream (IQ), a new method for predicting gene regulation from DNA sequence using physical models of transcription factor binding. IQ offers a mechanistic and interpretable alternative to deep learning, achieving comparable performance.

More Related Videos

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

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

Published on: November 13, 2017

ATAC-Seq Optimization for Cancer Epigenetics Research

ATAC-Seq Optimization for Cancer Epigenetics Research

Published on: June 30, 2022

Related Experiment Videos

Last Updated: Jan 15, 2026

Formaldehyde-assisted Isolation of Regulatory Elements to Measure Chromatin Accessibility in Mammalian Cells

Formaldehyde-assisted Isolation of Regulatory Elements to Measure Chromatin Accessibility in Mammalian Cells

Published on: April 2, 2018

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

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

Published on: November 13, 2017

ATAC-Seq Optimization for Cancer Epigenetics Research

ATAC-Seq Optimization for Cancer Epigenetics Research

Published on: June 30, 2022

Area of Science:

Genomics
Computational Biology
Epigenetics

Background:

Single-cell sequencing reveals chromosomal accessibility patterns, improving epigenomic prediction from DNA sequence.
Current quantitative models lack interpretable components for epigenome explanation.
Predictive modeling of epigenomic activity from sequence is an active research area.

Purpose of the Study:

To develop a novel modeling strategy and inference algorithm for regressing accessibility from sequences using physical models of transcription factor (TF) binding.
To create a mechanistic and interpretable baseline for understanding gene and genome regulation from sequence.
To infer TF effective concentrations and their interactions.

Main Methods:

IceQream (IQ) employs spatial integration of sequences across TF-DNA affinities and localization relative to target loci.
IQ infers TF effective concentrations as latent variables, modeling non-linear activation/repression of regulatory elements.
Synergistic and antagonistic pairwise TF interactions are incorporated.

Main Results:

IQ demonstrates performance comparable or superior to state-of-the-art deep neural network models on human and mouse data.
The model successfully infers TF effective concentrations and their interactions.
IQ provides interpretable components for epigenome modeling.

Conclusions:

IQ offers a mechanistic and explicable approach to modeling epigenomic activity from sequence.
This method serves as a valuable baseline for future research in gene regulation.
IQ advances the understanding of how DNA sequence dictates regulatory element function.