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

14.8K
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...
14.8K
Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

6.5K
Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
6.5K
Comparing Copy Number Variations and SNPs02:26

Comparing Copy Number Variations and SNPs

18.2K
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%...
18.2K
Single Nucleotide Polymorphisms-SNPs01:05

Single Nucleotide Polymorphisms-SNPs

17.1K
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,...
17.1K

You might also read

Related Articles

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

Sort by
Same author

Mass Drug Administration With High-Dose Ivermectin and Dihydroartemisinin-Piperaquine for Malaria Elimination in an Area of Low Transmission With High Coverage of Malaria Control Interventions: Protocol for the MASSIV Cluster Randomized Clinical Trial.

JMIR research protocols·2020
Same author

First Report of Mature Citrus Trees Being Affected by Fusarium Wilt in Tunisia.

Plant disease·2019
Same author

Effects of arbuscular mycorrhizal inoculation and fertilization on mycorrhizal Statute of Jacaranda mimosifolia D.Don cultivated in nurseries.

Comptes rendus biologies·2013
Same author

Protective effect of Bacillus amyloliquefaciens against infections of Citrus aurantium seedlings by Phoma tracheiphila.

World journal of microbiology & biotechnology·2013
Same author

DNA sequence and comparative analysis of chimpanzee chromosome 22.

Nature·2004

Related Experiment Video

Updated: Oct 31, 2025

Identification and Classification of Position-specific GABAA Receptor Subunit Missense Variants for Their Role In Hippocampal Pyramidal Neurons
08:04

Identification and Classification of Position-specific GABAA Receptor Subunit Missense Variants for Their Role In Hippocampal Pyramidal Neurons

Published on: June 6, 2025

719

New neural network classification method for individuals ancestry prediction from SNPs data.

H Soumare1,2, S Rezgui3, N Gmati4

  • 1The Laboratory of Mathematical Modelling and Numeric in Engineering Sciences, National Engineering School of Tunis, Rue Béchir Salem Belkhiria Campus universitaire, B.P. 37, 1002 Tunis Belvédère, University of Tunis El Manar, Tunis, Tunisia. soumare.harouna@enit.utm.tn.

Biodata Mining
|June 29, 2021
PubMed
Summary

This study introduces a new Artificial Neural Network (ANN) method for analyzing genomic data, specifically Single Nucleotide Polymorphisms (SNPs), to improve disease prediction accuracy despite high dimensionality and limited samples.

Keywords:
Artificial neural networkDimensionality reductionInput perturbationSingle nucleotide polymorphismSingular value decomposition

More Related Videos

Mapping Alzheimer's Disease Variants to Their Target Genes Using Computational Analysis of Chromatin Configuration
04:41

Mapping Alzheimer's Disease Variants to Their Target Genes Using Computational Analysis of Chromatin Configuration

Published on: January 9, 2020

19.1K
Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease
09:34

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease

Published on: April 4, 2018

34.2K

Related Experiment Videos

Last Updated: Oct 31, 2025

Identification and Classification of Position-specific GABAA Receptor Subunit Missense Variants for Their Role In Hippocampal Pyramidal Neurons
08:04

Identification and Classification of Position-specific GABAA Receptor Subunit Missense Variants for Their Role In Hippocampal Pyramidal Neurons

Published on: June 6, 2025

719
Mapping Alzheimer's Disease Variants to Their Target Genes Using Computational Analysis of Chromatin Configuration
04:41

Mapping Alzheimer's Disease Variants to Their Target Genes Using Computational Analysis of Chromatin Configuration

Published on: January 9, 2020

19.1K
Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease
09:34

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease

Published on: April 4, 2018

34.2K

Area of Science:

  • Genomics
  • Bioinformatics
  • Machine Learning

Background:

  • Artificial Neural Network (ANN) algorithms are utilized for genomic data analysis.
  • Single Nucleotide Polymorphisms (SNPs) are common genetic variations linked to diseases and prediction.
  • High dimensionality and limited samples complicate genomic data learning tasks.

Purpose of the Study:

  • To propose a novel Neural Network classification method for genomic data analysis.
  • To address challenges posed by high dimensionality and limited sample sizes in genomic datasets.
  • To enhance the accuracy of disease prediction using genetic variations.

Main Methods:

  • Utilized Singular Value Decomposition (SVD) for input data dimensionality reduction.
  • Developed a classification network trained on reduced-dimension genomic data.
  • Implemented input perturbation by modifying the SVD projection matrix to minimize prediction errors.

Main Results:

  • The proposed method demonstrated effectiveness on genomic data from diverse ancestral origins.
  • Achieved a classification accuracy of up to 96.23%.
  • Outperformed previous Deep Learning approaches on the same dataset.

Conclusions:

  • The novel ANN approach effectively handles high-dimensional genomic data with limited samples.
  • Input perturbation combined with SVD offers a robust strategy for improving classification accuracy.
  • This method shows significant potential for advancing genetic disease prediction and analysis.