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-protein Interfaces02:04

Protein-protein Interfaces

15.0K
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...
15.0K
Conserved Binding Sites01:49

Conserved Binding Sites

5.3K
Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
Binding sites are often located in large pockets, and if their location on a protein’s surface is unknown, it can be predicted using various approaches. The energetic method computationally...
5.3K
Protein Networks02:26

Protein Networks

4.7K
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,...
4.7K

You might also read

Related Articles

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

Sort by
Same author

Quantitative modulation of a spatial enhancer through the biophysical properties of a transcription factor binding site.

Science advances·2026
Same author

Accurate affinity models for SH2 domains from peptide binding assays and free-energy regression.

Protein science : a publication of the Protein Society·2025
Same author

FETCH enables fluorescent labeling of membrane proteins in vivo with spatiotemporal control in <i>Drosophila</i>.

Proceedings of the National Academy of Sciences of the United States of America·2025
Same author

A critical affinity window for IgSF proteins DIP-α and Dpr10 is required for proper motor neuron arborization.

Genes & development·2025
Same author

Predicting the DNA binding specificity of transcription factor mutants using family-level biophysically interpretable machine learning.

Nucleic acids research·2025
Same author

Decoding neuronal wiring by joint inference of cell identity and synaptic connectivity.

bioRxiv : the preprint server for biology·2025

Related Experiment Video

Updated: Mar 28, 2026

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions
06:50

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions

Published on: January 26, 2024

2.7K

Building accurate sequence-to-affinity models from high-throughput in vitro protein-DNA binding data using

Todd R Riley1,2,3, Allan Lazarovici1,4, Richard S Mann2,5

  • 1Department of Biological Sciences, Columbia University, New York, United States.

Elife
|December 25, 2015
PubMed
Summary

FeatureREDUCE accurately models transcription factor DNA binding preferences. This framework improves understanding of gene regulation by analyzing high-throughput data with greater precision.

Keywords:
DNA binding specificitybiophysical modelcomputational biologynoneprotein binding microarray technologysystems biologytranscription factor

More Related Videos

Biosensor-based High Throughput Biopanning and Bioinformatics Analysis Strategy for the Global Validation of Drug-protein Interactions
08:31

Biosensor-based High Throughput Biopanning and Bioinformatics Analysis Strategy for the Global Validation of Drug-protein Interactions

Published on: December 1, 2020

5.6K
DNA Sequence Recognition by DNA Primase Using High-Throughput Primase Profiling
08:04

DNA Sequence Recognition by DNA Primase Using High-Throughput Primase Profiling

Published on: October 8, 2019

9.2K

Related Experiment Videos

Last Updated: Mar 28, 2026

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions
06:50

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions

Published on: January 26, 2024

2.7K
Biosensor-based High Throughput Biopanning and Bioinformatics Analysis Strategy for the Global Validation of Drug-protein Interactions
08:31

Biosensor-based High Throughput Biopanning and Bioinformatics Analysis Strategy for the Global Validation of Drug-protein Interactions

Published on: December 1, 2020

5.6K
DNA Sequence Recognition by DNA Primase Using High-Throughput Primase Profiling
08:04

DNA Sequence Recognition by DNA Primase Using High-Throughput Primase Profiling

Published on: October 8, 2019

9.2K

Area of Science:

  • Molecular Biology
  • Genomics
  • Bioinformatics

Background:

  • Transcription factors regulate gene expression by binding to specific DNA sequences.
  • Understanding transcription factor DNA binding is essential for deciphering gene regulation.
  • Existing algorithms for analyzing high-throughput DNA binding data require further development.

Purpose of the Study:

  • To develop a robust computational framework for building accurate sequence-to-affinity models of protein-DNA interactions.
  • To improve the analysis of high-throughput data for determining transcription factor binding specificity.
  • To provide a biophysically interpretable and extensible model for protein-DNA binding.

Main Methods:

  • Developed FeatureREDUCE, a novel framework for sequence-to-affinity modeling.
  • Employed robust regression techniques for model training.
  • Incorporated modeling of technology-specific biases inherent in high-throughput data.
  • Utilized protein binding microarray (PBM) data for model training and validation.

Main Results:

  • FeatureREDUCE infers transcription factor binding specificity models with high accuracy and precision.
  • The framework accounts for nucleotide dependencies and multiple binding modes.
  • Models generated by FeatureREDUCE demonstrate superior performance compared to existing methods.
  • Quantitative validation confirmed the reliability of the inferred specificity models.

Conclusions:

  • FeatureREDUCE offers a significant advancement in analyzing transcription factor DNA binding data.
  • The framework enhances the quantitative definition of transcription factor binding preferences.
  • Accurate binding models are critical for understanding gene regulation and biological function.