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

Mutation, Gene Flow, and Genetic Drift01:09

Mutation, Gene Flow, and Genetic Drift

65.0K
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).
65.0K
Viral Mutations00:36

Viral Mutations

40.1K
A mutation is a change in the sequence of bases of DNA or RNA in a genome. Some mutations occur during replication of the genome due to errors made by the polymerase enzymes that replicate DNA or RNA. Unlike DNA polymerase, RNA polymerase is prone to errors because it is not capable of “proofreading” its work. Viruses with RNA-based genomes, like HIV, therefore accrue mutations faster than viruses with DNA-based genomes. Because mutation and recombination provide the raw material...
40.1K
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

375
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
375
Genetic Drift03:33

Genetic Drift

44.5K
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.
44.5K
Conservative Site-specific Recombination and Phase Variation02:53

Conservative Site-specific Recombination and Phase Variation

7.0K
Because the DNA segments are cut and reorganized in a direction-specific manner, site-specific recombination has emerged as an efficient genetic engineering technique. Flippase and Cyclization recombinases or Flp and Cre, respectively, are two members of the tyrosine recombinase family derived from bacteriophages, that are used to mediate site-specific DNA insertions, deletions, and targeted expression of proteins in mammalian cell lines.
The recognition sites for Cre recombinase called LoxP...
7.0K
Viral Recombination00:57

Viral Recombination

25.4K
Cells are sometimes infected by more than one virus at once. When two viruses disassemble to expose their genomes for replication in the same cell, similar regions of their genomes can pair together and exchange sequences in a process called recombination. Alternatively, viruses with segmented genomes can swap segments in a process called reassortment.
25.4K

You might also read

Related Articles

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

Sort by
Same author

Cdc42-Modified BMSC-Derived exosomes promote acellular nerve allografts to bridge sciatic nerve defects.

Cell transplantation·2026
Same author

The RNA-binding protein RBFOX2 suppresses colorectal cancer proliferation and metastasis by reducing FUBP1 mRNA stability to induce mitochondrial dysfunction and ferroptosis.

Discover oncology·2026
Same author

BMSC-Derived Exosomal miR-874-3p Protects against OGD/R-Induced Neuronal Injury in PC12 Cells via Regulating KPNA4.

Neurochemical research·2026
Same author

Lithophilic yet Inert Interfaces Strategy for Stable Lithium Metal Anodes.

ACS nano·2026
Same author

The role of neuroendocrine differentiation in treatment resistance of prostate cancer and intervention strategies.

Frontiers in oncology·2026
Same author

Biomechanical comparison of five fixation methods in minimally invasive hallux valgus osteotomy: a three-dimensional finite element analysis.

Frontiers in medicine·2025
Same journal

RETRACTION: Real-Time Modulation of Physical Training Intensity Based on Wavelet Recursive Fuzzy Neural Networks.

Computational intelligence and neuroscience·2026
Same journal

RETRACTION: Multidimensional Heterogeneous Network Link Adaptation Based on Mobile Environment.

Computational intelligence and neuroscience·2026
Same journal

RETRACTION: Framework to Segment and Evaluate Multiple Sclerosis Lesion in MRI Slices Using VGG-UNet.

Computational intelligence and neuroscience·2026
Same journal

RETRACTION: Facial Emotion Recognition Using a Novel Fusion of Convolutional Neural Network and Local Binary Pattern in Crime Investigation.

Computational intelligence and neuroscience·2026
Same journal

RETRACTION: Automatic Intelligent System Using Medical of Things for Multiple Sclerosis Detection.

Computational intelligence and neuroscience·2026
Same journal

RETRACTION: Intangible Cultural Heritage Reproduction and Revitalization: Value Feedback, Practice, and Exploration Based on the IPA Model.

Computational intelligence and neuroscience·2026
See all related articles

Related Experiment Video

Updated: Mar 3, 2026

Following the Dynamics of Structural Variants in Experimentally Evolved Populations
04:52

Following the Dynamics of Structural Variants in Experimentally Evolved Populations

Published on: February 3, 2023

1.4K

Memetic Differential Evolution with an Improved Contraction Criterion.

Lei Peng1,2, Yanyun Zhang1, Guangming Dai1,2

  • 1School of Computer Science, China University of Geosciences, No. 388 Lumo Road, Hongshan District, Wuhan, China.

Computational Intelligence and Neuroscience
|May 6, 2017
PubMed
Summary
This summary is machine-generated.

This study introduces an improved memetic differential evolution (MDE) algorithm for global optimization. MDE effectively balances exploration and exploitation, demonstrating competitive performance against established evolutionary algorithms.

More Related Videos

Automated Microbial Cultivation and Adaptive Evolution using Microbial Microdroplet Culture System MMC
08:18

Automated Microbial Cultivation and Adaptive Evolution using Microbial Microdroplet Culture System MMC

Published on: February 18, 2022

4.6K
Quantification of Plasmid-Mediated Antibiotic Resistance in an Experimental Evolution Approach
12:32

Quantification of Plasmid-Mediated Antibiotic Resistance in an Experimental Evolution Approach

Published on: December 14, 2019

14.8K

Related Experiment Videos

Last Updated: Mar 3, 2026

Following the Dynamics of Structural Variants in Experimentally Evolved Populations
04:52

Following the Dynamics of Structural Variants in Experimentally Evolved Populations

Published on: February 3, 2023

1.4K
Automated Microbial Cultivation and Adaptive Evolution using Microbial Microdroplet Culture System MMC
08:18

Automated Microbial Cultivation and Adaptive Evolution using Microbial Microdroplet Culture System MMC

Published on: February 18, 2022

4.6K
Quantification of Plasmid-Mediated Antibiotic Resistance in an Experimental Evolution Approach
12:32

Quantification of Plasmid-Mediated Antibiotic Resistance in an Experimental Evolution Approach

Published on: December 14, 2019

14.8K

Area of Science:

  • Computational Intelligence
  • Optimization Algorithms
  • Evolutionary Computation

Background:

  • Memetic algorithms offer a robust framework for continuous optimization by balancing exploration and exploitation.
  • Differential Evolution (DE) is a powerful evolutionary algorithm, but its performance can be enhanced with local search strategies.

Purpose of the Study:

  • To introduce an improved memetic differential evolution (MDE) algorithm for global optimization problems.
  • To enhance the balance between exploration and exploitation in evolutionary optimization.
  • To propose a novel contraction criterion for initiating local search.

Main Methods:

  • Hybridization of Differential Evolution (DE) with a Local Search (LS) operator and periodic reinitialization.
  • Development of a new contraction criterion based on improved maximum distance in objective space to trigger local search.
  • Comparative analysis against six well-known evolutionary algorithms on twenty-one benchmark functions.

Main Results:

  • The proposed Memetic DE (MDE) algorithm demonstrates competitive performance compared to six established evolutionary algorithms.
  • Experimental results were rigorously analyzed using two types of nonparametric statistical tests.
  • Sensitivity analyses confirmed the robustness of MDE across its key parameters.

Conclusions:

  • The improved memetic differential evolution algorithm (MDE) offers a superior approach to global optimization.
  • MDE effectively balances exploration and exploitation, leading to enhanced performance.
  • The proposed contraction criterion is effective in determining the optimal timing for local search intensification.