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

4.6K
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,...
4.6K
Protein Networks02:26

Protein Networks

2.9K
2.9K
Protein-protein Interfaces02:04

Protein-protein Interfaces

14.8K
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...
14.8K
Protein-Protein Interfaces02:04

Protein-Protein Interfaces

4.5K
4.5K
Ligand Binding Sites02:40

Ligand Binding Sites

15.4K
Proteins are dynamic macromolecules that carry out a wide variety of essential processes; however, the activities of most proteins depend on their interactions with other molecules or ions, known as ligands.
Protein-ligand interactions are quite specific; even though numerous potential ligands surround a cellular protein at any given time, only a particular ligand can bind to that protein. Moreover, a ligand binds only to a dedicated area on the surface of the protein, known as the...
15.4K
Conserved Binding Sites01:49

Conserved Binding Sites

5.2K
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...
5.2K

You might also read

Related Articles

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

Sort by
Same author

A Comparative Effectiveness Study of Bipolar and Linked Quadripolar Techniques for Eliciting Transcranial Motor Evoked Potentials.

The Neurodiagnostic journal·2026
Same author

Equity and Respect in Maternal and Infant Healthcare-A Report From the 2025 Venice Forum.

Acta paediatrica (Oslo, Norway : 1992)·2026
Same author

Breaking the Triple Barrier to Equitable and Inclusive Pediatric Research and Innovation.

The Journal of pediatrics·2026
Same author

Integrating child mental health responses into recovery, development, and peacebuilding in fragile and conflict affected settings.

BMJ (Clinical research ed.)·2026
Same author

Beyond Social Conditions: The Moral Determinants of Children's Health.

The Journal of pediatrics·2026
Same author

Universal Decentralized Cord Blood TSH Screening Should Be Offered as Routine Delivery Care in Limited-Resource Settings.

International journal of neonatal screening·2025
Same journal

Analysis of strength degradation of coal and rock masses and stability of mined areas under long term immersion environment.

PloS one·2026
Same journal

Biogenic Silver-Selenium nanocomposite with anticancer activity and potent efficacy against vancomycin-resistant Staphylococcus aureus.

PloS one·2026
Same journal

Preparation and physicochemical characterization of a biodegradable chitosan/carboxymethyl cellulose hydrogel synthesized in NaOH/urea medium.

PloS one·2026
Same journal

Action-guilt, survivor-guilt, and depression in combat-related PTSD.

PloS one·2026
Same journal

Explainable machine learning for predicting activities of daily living at discharge in stroke patients: A retrospective study using SHAP interpretability.

PloS one·2026
Same journal

Deep learning based two-way feature depiction model for brain tumor detection.

PloS one·2026
See all related articles

Related Experiment Video

Updated: Feb 20, 2026

Genome-wide Protein-protein Interaction Screening by Protein-fragment Complementation Assay PCA in Living Cells
08:38

Genome-wide Protein-protein Interaction Screening by Protein-fragment Complementation Assay PCA in Living Cells

Published on: March 3, 2015

14.0K

Inferring gene and protein interactions using PubMed citations and consensus Bayesian networks.

Anthony Deeter1,2, Mark Dalman3,4, Joseph Haddad2

  • 1Integrated Bioscience, University of Akron, Akron, Ohio, United States of America.

Plos One
|October 20, 2017
PubMed
Summary
This summary is machine-generated.

We developed a computational method to analyze PubMed publications and infer gene interactions. This approach generates consensus networks, confirming known interactions and discovering novel ones, aiding biological pathway analysis.

More Related Videos

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports
07:35

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports

Published on: October 13, 2023

2.2K
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

3.7K

Related Experiment Videos

Last Updated: Feb 20, 2026

Genome-wide Protein-protein Interaction Screening by Protein-fragment Complementation Assay PCA in Living Cells
08:38

Genome-wide Protein-protein Interaction Screening by Protein-fragment Complementation Assay PCA in Living Cells

Published on: March 3, 2015

14.0K
A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports
07:35

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports

Published on: October 13, 2023

2.2K
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

3.7K

Area of Science:

  • Computational Biology
  • Bioinformatics
  • Systems Biology

Background:

  • PubMed database provides vast publication data, but its complexity necessitates automated computational techniques.
  • Genomic Data Commons (GDC) and Gene Expression Omnibus (GEO) offer experimental data, while Reactome and Ingenuity Pathway Analysis provide curated pathway and interaction data.

Purpose of the Study:

  • To develop and validate a novel computational method for inferring gene interactions from PubMed publication abstracts.
  • To generate and analyze consensus networks using Bayesian networks for robust gene interaction discovery.
  • To assess the stability and accuracy of the method across varying input sizes and network resolutions.

Main Methods:

  • Data mining of PubMed publication abstracts to generate large numbers of Bayesian networks.
  • Consensus network generation and analysis, tailored by network resolution.
  • Experimental validation using gene product interactions from KEGG pathway database and randomized topological orderings.

Main Results:

  • The method successfully infers meaningful gene interactions, confirming known pathways like JAK-STAT-PI3K-AKT-mTOR.
  • Novel gene interactions, such as RAS-Bcl-2 and RAS-AKT, were hypothesized.
  • Significant pathway-pathway interactions were identified between JAK-STAT signaling and Cardiac Muscle Contraction KEGG pathways.

Conclusions:

  • The developed method provides a stable and effective approach for inferring gene interactions from biomedical literature.
  • This computational strategy can confirm existing biological knowledge and generate new hypotheses for gene interactions.
  • The findings have implications for advancing our understanding of complex biological pathways and networks.