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

Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

12.6K
Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...
12.6K
Protein Networks02:26

Protein Networks

3.7K
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,...
3.7K
Protein Networks02:26

Protein Networks

1.8K
1.8K
Pharmacogenomics: Identification of New Drug Targets01:29

Pharmacogenomics: Identification of New Drug Targets

121
Advances in genomics have profoundly influenced drug discovery by increasing both the speed and accuracy of pharmaceutical development. Pharmacogenomics, which examines how genetic variation influences drug response, facilitates the identification of novel therapeutic targets and enables patient stratification for personalized treatment. These strategies contribute to improved drug efficacy, minimized adverse effects, and more efficient clinical trial design.Mapping genetic differences...
121
Investigation of Disease Outbreaks01:23

Investigation of Disease Outbreaks

74
Multistate foodborne outbreaks pose significant public health risks and require meticulous investigation to identify sources and implement control measures. The Centers for Disease Control and Prevention (CDC) utilizes a dynamic seven-step process for these investigations, integrating data from laboratories, interviews, and environmental assessments to protect public health.Outbreak Detection: The detection of multistate outbreaks typically begins with PulseNet, the CDC's national laboratory...
74

You might also read

Related Articles

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

Sort by
Same author

Ubiquitous impact of natural selection on nucleotide diversity in 178 species of primates.

Genome biology·2026
Same author

Long-read sequencing of primate testis and human sperm allows identification of recombination events in individuals.

Nature communications·2025
Same author

Cross-dataset pan-cancer detection by correlating cell-free DNA fragment coverage with open chromatin sites across cell types.

Nature communications·2025
Same author

Determinants of de novo mutations in extended pedigrees of 43 dog breeds.

Genome biology·2025
Same author

Rate of de novo mutations in the three-spined stickleback.

Heredity·2025
Same author

Genetic predictions of eye and hair colour in the Danish population.

Forensic science international. Genetics·2025

Related Experiment Video

Updated: May 2, 2026

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

2.6K

Identifying disease associated genes by network propagation.

Yu Qian, Søren Besenbacher, Thomas Mailund

    BMC Systems Biology
    |February 26, 2014
    PubMed
    Summary

    This study introduces a network propagation framework to enhance genome-wide association studies (GWAS). The method improves the identification of genes associated with complex diseases by analyzing protein-protein interaction networks.

    More Related Videos

    Discovery of Driver Genes in Colorectal HT29-derived Cancer Stem-Like Tumorspheres
    06:52

    Discovery of Driver Genes in Colorectal HT29-derived Cancer Stem-Like Tumorspheres

    Published on: July 22, 2020

    6.0K
    Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation
    07:15

    Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation

    Published on: January 16, 2019

    10.2K

    Related Experiment Videos

    Last Updated: May 2, 2026

    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

    2.6K
    Discovery of Driver Genes in Colorectal HT29-derived Cancer Stem-Like Tumorspheres
    06:52

    Discovery of Driver Genes in Colorectal HT29-derived Cancer Stem-Like Tumorspheres

    Published on: July 22, 2020

    6.0K
    Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation
    07:15

    Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation

    Published on: January 16, 2019

    10.2K

    Area of Science:

    • Genetics
    • Bioinformatics
    • Systems Biology

    Background:

    • Genome-wide association studies (GWAS) identify individual genes linked to complex traits.
    • Pathway and network information are underutilized in genetic determinant searches.
    • Integrating network data can deepen understanding of common disease biology.

    Purpose of the Study:

    • To develop a principled framework for integrating pathway and network information into GWAS.
    • To test the hypothesis that complex diseases involve multiple interconnected genes.
    • To improve the identification of genetic determinants for complex diseases.

    Main Methods:

    • Translating GWAS associations into prior scores for protein-protein interaction networks.
    • Propagating scores through the network to identify 'guilty-by-association' genes.
    • Utilizing permutation analysis to select consistently high-scoring genes after network propagation.

    Main Results:

    • Applied the framework to Crohn's disease data, identifying candidate genes previously unreported in the analyzed dataset but found in independent GWAS.
    • Developed a prediction model using candidate genes demonstrating strong predictive power (AUC).
    • The network propagation approach successfully identified relevant genes.

    Conclusions:

    • The proposed network propagation method, when applied to GWAS data, yields increased association findings compared to other methods.
    • This approach enhances the discovery of genetic associations for complex diseases.
    • It offers a more comprehensive understanding of disease genetics by leveraging network structures.