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

Genetic Variation01:25

Genetic Variation

Genetic variation is the diversity in DNA sequences found among individuals of the same species. This diversity is crucial for a species' survival because it helps organisms adapt to environmental changes. Genetic variation begins with fertilization, where an egg and sperm cell merge. Each of these cells carries 23 chromosomes, up to 46 in the fertilized egg. Chromosomes are long DNA strands that contain genes, the basic units of heredity.
Genes exist in different versions called alleles, which...
Genetic Screens02:46

Genetic Screens

Genetic screens are tools used to identify genes and mutations responsible for phenotypes of interest. Genetic screens help identify individuals or a group of people at risk of developing  genetic diseases and help them with early intervention, targeted therapy, and reproductive options.
Forward genetic screens
Forward or “classical” genetic screens involve creating random mutations in an organism’s DNA using radiation, mutagens, or insertion of additional bases, which result in visible changes...
Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

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...
Genetics of Speciation02:16

Genetics of Speciation

Speciation is the evolutionary process resulting in the formation of new, distinct species—groups of reproductively isolated populations.
Genetic Drift03:33

Genetic Drift

Natural selection—probably the most well-known evolutionary mechanism—increases the prevalence of traits that enhance survival and reproduction. However, evolution does not merely propagate favorable traits, nor does it always benefit populations.
Mutation, Gene Flow, and Genetic Drift01:09

Mutation, Gene Flow, and Genetic Drift

In a population that is not at Hardy-Weinberg equilibrium, the frequency of alleles changes over time. Therefore, any deviations from the five conditions of Hardy-Weinberg equilibrium can alter the genetic variation of a given population. Conditions that change the genetic variability of a population include mutations, natural selection, non-random mating, gene flow, and genetic drift (small population size).

You might also read

Related Articles

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

Sort by
Same author

eIF4E-Dependent Translation Potentially Regulates Apoptosis and BDNF/TrkB Signaling in the Medial Prefrontal Cortex During Morphine-Induced CPP.

International journal of molecular sciences·2026
Same author

Age Estimation of the Cervical Vertebrae Region Using Deep Learning.

Bioengineering (Basel, Switzerland)·2026
Same author

Novel LncRNA Gm44763 Regulates Morphine-Induced Reward Memory via MiR-298-5p-Mediated eIF4E Translation Control.

Research (Washington, D.C.)·2026
Same author

The clinical significance of circulating microRNAs as biomarkers in lung cancer diagnosis and prognosis.

Discover oncology·2025
Same author

Detection of disk-jet coprecession in a tidal disruption event.

Science advances·2025
Same author

LncRNA THUMPD3-AS1 Regulates Behavioral and Synaptic Structural Abnormalities in Schizophrenia via miR-485-5p and ARHGAP8.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2025

Related Experiment Video

Updated: May 8, 2026

In Vivo Modeling of the Morbid Human Genome using Danio rerio
12:31

In Vivo Modeling of the Morbid Human Genome using Danio rerio

Published on: August 24, 2013

Identifying interacting genetic variations by fish-swarm logic regression.

Xuanping Zhang1, Jiayin Wang, Aiyuan Yang

  • 1Department of Computer Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China.

Biomed Research International
|August 29, 2013
PubMed
Summary

Fish-Swarm Logic Regression (FSLR) enhances genotype-phenotype association studies. This novel approach uses swarm intelligence to improve accuracy and efficiency in identifying genetic variants contributing to complex traits.

More Related Videos

High-throughput DNA Extraction and Genotyping of 3dpf Zebrafish Larvae by Fin Clipping
10:12

High-throughput DNA Extraction and Genotyping of 3dpf Zebrafish Larvae by Fin Clipping

Published on: June 29, 2018

Genotyping and Quantification of In Situ Hybridization Staining in Zebrafish
05:41

Genotyping and Quantification of In Situ Hybridization Staining in Zebrafish

Published on: January 28, 2020

Related Experiment Videos

Last Updated: May 8, 2026

In Vivo Modeling of the Morbid Human Genome using Danio rerio
12:31

In Vivo Modeling of the Morbid Human Genome using Danio rerio

Published on: August 24, 2013

High-throughput DNA Extraction and Genotyping of 3dpf Zebrafish Larvae by Fin Clipping
10:12

High-throughput DNA Extraction and Genotyping of 3dpf Zebrafish Larvae by Fin Clipping

Published on: June 29, 2018

Genotyping and Quantification of In Situ Hybridization Staining in Zebrafish
05:41

Genotyping and Quantification of In Situ Hybridization Staining in Zebrafish

Published on: January 28, 2020

Area of Science:

  • Human Genetics
  • Computational Biology
  • Statistical Genetics

Background:

  • Identifying interacting genetic variants for complex traits is a challenge in human genetics.
  • Existing Logic Regression (LR) methods lack optimal accuracy and efficiency for phenotype mapping.
  • Advanced computational approaches are needed to improve the analysis of genotype-phenotype associations.

Purpose of the Study:

  • To introduce Fish-Swarm Logic Regression (FSLR), a novel approach to enhance genotype-phenotype association studies.
  • To improve the accuracy and efficiency of identifying genetic variants contributing to complex traits.
  • To overcome limitations of existing Logic Regression-based methods.

Main Methods:

  • Developed Fish-Swarm Logic Regression (FSLR) by integrating swarm optimization with Logic Regression.
  • Employed a parallelized school of fish agents, each holding a regression model, to search for optimal models.
  • Utilized preset swarm behaviors to enhance model convergence and avoid local optima.

Main Results:

  • FSLR demonstrated superior performance compared to three existing LR-based approaches.
  • The proposed method achieved lower type I and type II error rates in association studies.
  • FSLR successfully identified more predefined causal genetic sites and operated at significantly faster speeds.

Conclusions:

  • Fish-Swarm Logic Regression (FSLR) offers a more accurate and efficient solution for identifying genetic variants associated with complex traits.
  • The integration of swarm intelligence significantly improves upon traditional Logic Regression methods.
  • FSLR provides a promising tool for advancing genotype-phenotype association studies in human genetics.