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

Epistasis Analysis01:09

Epistasis Analysis

5.1K
Although Mendel chose seven unrelated traits in peas to study gene segregation, most traits involve multiple gene interactions that create a spectrum of phenotypes. When the interaction of various genes or alleles at different locations influences a phenotype, this is called epistasis. Epistasis often involves one gene masking or interfering with the expression of another (antagonistic epistasis). Epistasis often occurs when different genes are part of the same biochemical pathway. The...
5.1K
Protein Networks02:26

Protein Networks

4.1K
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,...
4.1K
Protein-protein Interfaces02:04

Protein-protein Interfaces

12.6K
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...
12.6K
Gene-Environment Interactions01:20

Gene-Environment Interactions

407
Gene expression is a dynamic process that is significantly influenced by environmental factors. This interaction underlies the complex nature of biological development and the phenotypic differences observed among individuals, even among those with identical genetic makeups. Factors such as radiation, temperature, behavior, nutrition, and stress play pivotal roles in determining how genes are expressed. The concept of the reaction range is central to understanding this interaction. It posits...
407
Reporter Genes02:11

Reporter Genes

11.7K
Reporter genes are a type of protein-coding gene that are often tagged to a gene of interest. Once inside a target cell, reporter genes usually produce visually identifiable characteristics like fluorescence and luminescence when expressed along with the gene of interest. Thus, reporter genes “report” the presence or absence of genes of interest in an organism, determine the gene expression pattern, or track the physical location of a DNA segment or protein in the cell.
11.7K

You might also read

Related Articles

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

Sort by
Same author

Lactic acid bacteria and endogenous ethanol mediate proton pump inhibitor-associated MASLD: a multicohort cross-sectional mediation analysis.

Gut microbes·2026
Same author

Personalized Glucose Management With AI: Pilot Study Using a Multiarmed Bandit Approach.

JMIR formative research·2026
Same author

The impact of the Social Exposome in Cardiovascular Health and Disease.

Journal of precision medicine (Amsterdam, Netherlands)·2026
Same author

KANN: estimation of genetic ancestry profiles by nearest neighbor regression.

Nucleic acids research·2026
Same author

Screening for Celiac Disease in Childhood: Cost-Effectiveness of Multiple Genetic and Serological Testing Approaches.

Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association·2025
Same author

Value of Multiomics Over Clinical Risk Factors in Hypertension Prediction.

Hypertension (Dallas, Tex. : 1979)·2025
Same journal

Salt priming coordinates transcriptional and epigenetic states for enhanced salt tolerance in mung bean (Vigna radiata).

Communications biology·2026
Same journal

A male-derived volatile sex pheromone in Caenorhabditis nematodes identified through its mimicry by a predator.

Communications biology·2026
Same journal

Revalidation of Manis aurita based on integrative genomic and morphological evidence.

Communications biology·2026
Same journal

Presenilin-1 controls glycolysis and identity of pancreatic beta cells.

Communications biology·2026
Same journal

Base editing-derived models of human WDR34 and WDR60 disease alleles replicate retrograde intraflagellar transport (IFT) and hedgehog signaling defects.

Communications biology·2026
Same journal

Butterflies with low thermoregulatory capacity show greatest upwards range shifts along an elevational gradient.

Communications biology·2026
See all related articles

Related Experiment Video

Updated: Aug 22, 2025

DNA Virus Detection System Based on RPA-CRISPR/Cas12a-SPM and Deep Learning
04:17

DNA Virus Detection System Based on RPA-CRISPR/Cas12a-SPM and Deep Learning

Published on: May 10, 2024

844

Gene-gene interaction detection with deep learning.

Tianyu Cui1, Khaoula El Mekkaoui2, Jaakko Reinvall2

  • 1Department of Computer Science, Aalto University, Espoo, Finland. tianyu.cui@aalto.fi.

Communications Biology
|November 13, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces a new framework to detect complex genetic interactions affecting phenotypes by analyzing all SNPs within genes. The method successfully identified significant genetic interactions for cholesterol, improving upon existing approaches.

More Related Videos

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches
09:47

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

Published on: December 15, 2023

1.2K
Informatic Analysis of Sequence Data from Batch Yeast 2-Hybrid Screens
09:14

Informatic Analysis of Sequence Data from Batch Yeast 2-Hybrid Screens

Published on: June 28, 2018

7.2K

Related Experiment Videos

Last Updated: Aug 22, 2025

DNA Virus Detection System Based on RPA-CRISPR/Cas12a-SPM and Deep Learning
04:17

DNA Virus Detection System Based on RPA-CRISPR/Cas12a-SPM and Deep Learning

Published on: May 10, 2024

844
Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches
09:47

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

Published on: December 15, 2023

1.2K
Informatic Analysis of Sequence Data from Batch Yeast 2-Hybrid Screens
09:14

Informatic Analysis of Sequence Data from Batch Yeast 2-Hybrid Screens

Published on: June 28, 2018

7.2K

Area of Science:

  • Genetics
  • Bioinformatics
  • Computational Biology

Background:

  • Current genetic interaction detection methods are limited, focusing only on top SNPs and simple multiplicative relationships.
  • The impact of complex genetic interactions on observed phenotypes remains largely uncharacterized.
  • Discovering complex gene-gene interactions is crucial for understanding disease etiology.

Purpose of the Study:

  • To develop and validate an open-source framework for enhanced detection of complex genetic interactions.
  • To move beyond simple SNP-SNP interactions and multiplicative models in genetic association studies.
  • To improve the power and accuracy of identifying gene-gene interactions influencing phenotypes.

Main Methods:

  • Utilized a neural network to model the relationship between all SNPs within selected genes and phenotypes.
  • Employed Shapley scores between hidden nodes (gene representations) to quantify complex interactions.
  • Developed a novel permutation procedure for assessing the statistical significance of neural network-derived interactions.

Main Results:

  • The proposed framework demonstrated superior performance in detecting complex interactions on simulated data compared to existing methods.
  • In a UK Biobank cholesterol study, nine significant genetic interactions were identified.
  • These nine interactions showed replication in an independent FINRISK dataset, confirming their biological relevance.

Conclusions:

  • The novel framework significantly enhances the power to detect complex genetic interactions.
  • This approach provides a more comprehensive understanding of the genetic architecture of complex traits.
  • The findings have implications for genetic association studies and personalized medicine.