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

15.1K
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...
15.1K
Single Nucleotide Polymorphisms-SNPs01:05

Single Nucleotide Polymorphisms-SNPs

17.6K
A single nucleotide polymorphism or SNP is a single nucleotide variation at a specific genomic position in a large population. It is the most prevalent type of sequence variation found in the human genome. Point mutations that occur in more than 1% of the population qualify as SNPs. These are present once every 1000 nucleotides on an average in the human genome. Replacement of a purine with another purine (A/G) or a pyrimidine with another pyrimidine (C/T) is known as a transition. In contrast,...
17.6K
Comparing Copy Number Variations and SNPs02:26

Comparing Copy Number Variations and SNPs

18.4K
Sequencing of the human genome has opened up several best-kept secrets of the genome. Scientists have identified thousands of genome variations that exist within a population. These variations can be a single nucleotide or a larger chromosomal variation.
Copy number variations or CNVs are the structural variations that cover more than 1kb of DNA sequence. The single nucleotide polymorphism (SNP), on the other hand, is a single nucleotide change or a point mutation that is found in more than 1%...
18.4K

You might also read

Related Articles

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

Sort by
Same author

Network embedding framework for driver gene discovery by combining functional and structural information.

BMC genomics·2023
Same author

MGCNRF: Prediction of Disease-Related miRNAs Based on Multiple Graph Convolutional Networks and Random Forest.

IEEE transactions on neural networks and learning systems·2023
Same author

GCCN: Graph Capsule Convolutional Network for Progressive Mild Cognitive Impairment Prediction and Pathogenesis Identification Based on Imaging Genetic Data.

IEEE journal of biomedical and health informatics·2023
Same author

Automatic Code Review by Learning the Structure Information of Code Graph.

Sensors (Basel, Switzerland)·2023
Same author

EpiReSIM: A Resampling Method of Epistatic Model without Marginal Effects Using Under-Determined System of Equations.

Genes·2022
Same author

MDSN: A Module Detection Method for Identifying High-Order Epistatic Interactions.

Genes·2022
Same journal

Resveratrol Mitigates Noise-Induced Cochlear Damage and Delays Hearing Loss in Wistar Rats.

BioMed research international·2026
Same journal

RETRACTION: Green Fabrication of Silver Nanoparticles Using Euphorbia Serpens Kunth Aqueous Extract, their Characterization, and Investigation of its in Vitro Antioxidative, Antimicrobial, Insecticidal, and Cytotoxic Activities.

BioMed research international·2026
Same journal

Predictors of Prolonged Hospital Length of Stay in Patients With Odontogenic Infections in Ghana.

BioMed research international·2026
Same journal

Traditional Chinese Medicine Bone-Setting Techniques Research Progress for the Treatment of Knee Osteoarthritis.

BioMed research international·2026
Same journal

RETRACTION: miR-375 Inhibits the Proliferation and Invasion of Nasopharyngeal Carcinoma Cells by Suppressing PDK1.

BioMed research international·2026
Same journal

Exploring the Therapeutic Potential of Nobiletin in Nonsmall Cell Lung Cancer.

BioMed research international·2026
See all related articles

Related Experiment Video

Updated: Dec 9, 2025

Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA
11:35

Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA

Published on: August 21, 2016

13.3K

SAMA: A Fast Self-Adaptive Memetic Algorithm for Detecting SNP-SNP Interactions Associated with Disease.

Ying Yin1, Boxin Guan1, Yuhai Zhao1

  • 1Key Laboratory of Intelligent Computing in Medical Image, Minister of Education, and School of Computer Science and Engineering, Northeastern University, Shenyang 110819, China.

Biomed Research International
|September 10, 2020
PubMed
Summary
This summary is machine-generated.

This study introduces a fast self-adaptive memetic algorithm (SAMA) for detecting gene interactions in genome-wide association studies (GWAS). SAMA significantly improves detection power and reduces running time compared to existing methods.

More Related Videos

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
05:53

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Published on: June 21, 2018

10.5K
Rare Event Detection Using Error-corrected DNA and RNA Sequencing
10:36

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Published on: August 3, 2018

12.4K

Related Experiment Videos

Last Updated: Dec 9, 2025

Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA
11:35

Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA

Published on: August 21, 2016

13.3K
Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
05:53

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Published on: June 21, 2018

10.5K
Rare Event Detection Using Error-corrected DNA and RNA Sequencing
10:36

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Published on: August 3, 2018

12.4K

Area of Science:

  • Genetics
  • Bioinformatics
  • Computational Biology

Background:

  • Detecting single nucleotide polymorphism (SNP)-SNP interactions is crucial for understanding complex diseases in genome-wide association studies (GWAS).
  • Existing GWAS methods face challenges with computational intensity and limited detection power for SNP-SNP interactions.
  • Diversity in disease models further complicates the accurate identification of these genetic interactions.

Purpose of the Study:

  • To propose a novel, efficient algorithm for detecting SNP-SNP interactions associated with diseases.
  • To address the limitations of existing methods in terms of computational burden and detection accuracy.
  • To enhance the performance of genome-wide association studies through improved interaction detection.

Main Methods:

  • Development of a fast self-adaptive memetic algorithm (SAMA) specifically designed for SNP-SNP interaction detection.
  • Improvement of standard memetic algorithm components (crossover, mutation, selection) for adaptive disease association detection.
  • Integration of a self-adaptive local search algorithm to boost the method's detecting power.

Main Results:

  • SAMA demonstrated superior performance in detecting SNP-SNP interactions compared to four other contemporary evolutionary algorithms.
  • Experimental results on simulated and real-world datasets confirmed SAMA's enhanced detection power.
  • SAMA significantly reduced the running time required for identifying disease-associated SNP-SNP interactions.

Conclusions:

  • The proposed SAMA algorithm offers a more powerful and time-efficient solution for detecting SNP-SNP interactions in GWAS.
  • SAMA's adaptive features enable it to effectively handle diverse disease models and complex genetic architectures.
  • This advancement in computational methods holds significant promise for accelerating genetic research in complex diseases.