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

Protein Networks02:26

Protein Networks

3.9K
An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
3.9K
Protein-protein Interfaces02:04

Protein-protein Interfaces

12.5K
Many proteins form complexes to carry out their functions, making protein-protein interactions (PPIs) essential for an organism's survival. Most PPIs are stabilized by numerous weak noncovalent chemical forces. The physical shape of the interfaces determines the way two proteins interact. Many globular proteins have closely-matching shapes on their surfaces, which form a large number of weak bonds. Additionally, many PPIs occur between two helices or between a surface cleft and a...
12.5K
Interactions Between Signaling Pathways01:19

Interactions Between Signaling Pathways

6.3K
Signaling cascades usually lack linearity. Multiple pathways interact and regulate one another, allowing cells to integrate and respond to diverse environmental stimuli.
Convergence and divergence, and cross-talk between signaling pathways
Two distinct signaling pathways can converge on a single functional unit, which may either be a single protein or a complex of proteins. The response is either functionally distinct or synergistic between the two pathways but different from the response...
6.3K

You might also read

Related Articles

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

Sort by
Same author

Comparative Analysis of Transcription Factor Binding Sites in the Long Control Region Across Human Papillomavirus Types.

Viruses·2026
Same author

eSIG-Net: an interaction language model that decodes the protein code of single mutations.

Nature methods·2026
Same author

SRSF1 shapes 3'-end site selection with differential dependence on U1 snRNP.

bioRxiv : the preprint server for biology·2026
Same author

Distinctive DNA sequence features define epigenetic longevity of inflammatory memory.

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

Distinct mural cells and fibroblasts drive fibrochondrogenesis in retrodiscal tissue following temporomandibular joint disc displacement.

JCI insight·2026
Same author

Knowledge and attitudes of family members of cancer patients towards immunotherapy toxicity and health management.

Human vaccines & immunotherapeutics·2026

Related Experiment Video

Updated: Jun 21, 2025

Analyzing Tumor Gene Expression Factors with the CorExplorer Web Portal
08:00

Analyzing Tumor Gene Expression Factors with the CorExplorer Web Portal

Published on: October 11, 2019

7.5K

A large-scale cancer-specific protein-DNA interaction network.

Yunwei Lu1, Anna Berenson1,2, Ryan Lane1

  • 1Biology Department, Boston University, Boston, MA, USA.

Life Science Alliance
|July 16, 2024
PubMed
Summary

This study maps cancer gene transcription factor (TF) interactions, revealing TFs linked to patient outcomes. It identifies therapeutic targets, particularly for repressing oncogenes, and explores TF structural roles in gene regulation.

More Related Videos

Genome-wide Mapping of Drug-DNA Interactions in Cells with COSMIC Crosslinking of Small Molecules to Isolate Chromatin
10:05

Genome-wide Mapping of Drug-DNA Interactions in Cells with COSMIC Crosslinking of Small Molecules to Isolate Chromatin

Published on: January 20, 2016

8.3K
JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
07:28

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics

Published on: October 19, 2021

3.1K

Related Experiment Videos

Last Updated: Jun 21, 2025

Analyzing Tumor Gene Expression Factors with the CorExplorer Web Portal
08:00

Analyzing Tumor Gene Expression Factors with the CorExplorer Web Portal

Published on: October 11, 2019

7.5K
Genome-wide Mapping of Drug-DNA Interactions in Cells with COSMIC Crosslinking of Small Molecules to Isolate Chromatin
10:05

Genome-wide Mapping of Drug-DNA Interactions in Cells with COSMIC Crosslinking of Small Molecules to Isolate Chromatin

Published on: January 20, 2016

8.3K
JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
07:28

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics

Published on: October 19, 2021

3.1K

Area of Science:

  • Molecular Biology
  • Genetics
  • Cancer Research
  • Bioinformatics

Background:

  • Gene dysregulation, driven by transcription factor (TF) alterations, is central to cancer development.
  • Identifying key TFs in cancer gene regulation is crucial for developing novel therapeutic strategies.
  • Understanding TF-DNA interactions provides a foundation for targeted cancer treatments.

Purpose of the Study:

  • To construct a large-scale cancer gene TF-DNA interaction network.
  • To identify potential therapeutic targets by analyzing TF roles in cancer prognosis.
  • To investigate the functional significance of intrinsically disordered regions in cancer-related TFs.

Main Methods:

  • Development of a comprehensive TF-DNA interaction network using bioinformatics approaches.
  • Analysis of TF connectivity in relation to cancer gene promoters and patient prognosis.
  • Experimental investigation of intrinsically disordered regions in the ESR1 transcription factor.

Main Results:

  • A large-scale network revealed highly connected TFs associated with both favorable and unfavorable cancer prognoses.
  • Half of tested oncogenes showed potential for repression via modulation of specific activators or bifunctional TFs.
  • Intrinsically disordered regions in ESR1 demonstrated complex roles in DNA binding and transcriptional activity.

Conclusions:

  • The study provides a valuable resource for understanding TFs in cancer gene regulation.
  • Findings suggest therapeutic strategies targeting gene expression balance may be complex but offer oncogene repression potential.
  • Insights into TF structure-function relationships, like those in ESR1, can inform future drug development.