Jove
Visualize
Contact Us

Related Concept Videos

Crossing Over01:34

Crossing Over

172.1K
Unlike mitosis, meiosis aims for genetic diversity in its creation of haploid gametes. Dividing germ cells first begin this process in prophase I, where each chromosome—replicated in S phase—is now composed of two sister chromatids (identical copies) joined centrally.
The homologous pairs of sister chromosomes—one from the maternal and one from the paternal genome—then begin to align alongside each other lengthwise, matching corresponding DNA positions in a process...
172.1K
Crossing Over01:30

Crossing Over

6.5K
Crossing over is the exchange of genetic information between homologous chromosomes during prophase I of meiosis I. Genetic recombination gives rise to allelic diversity in the newly formed daughter cells. In humans, crossing over produces genetically distinct haploid egg and sperm cells that undergo fertilization to produce unique offspring. Before cell division starts, the germ cell’s chromosome(s) undergo duplication in the S phase of the cell cycle. As the cells enter prophase I,...
6.5K
Monohybrid Crosses01:20

Monohybrid Crosses

239.6K
Overview
239.6K
Dihybrid Crosses01:18

Dihybrid Crosses

81.3K
Overview
81.3K
Cross-Sectional Research01:50

Cross-Sectional Research

12.5K
In cross-sectional research, a researcher compares multiple segments of the population at the same time. If they were interested in people's dietary habits, the researcher might directly compare different groups of people by age. Instead of following a group of people for 20 years to see how their dietary habits changed from decade to decade, the researcher would study a group of 20-year-old individuals and compare them to a group of 30-year-old individuals and a group of 40-year-old...
12.5K
Test Cross01:39

Test Cross

44.2K
Alleles are different forms of the same gene. Humans and other diploid organisms inherit two alleles of every gene, one from each parent.
44.2K

You might also read

Related Articles

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

Sort by
Same journal

Formalising privacy regulations with bigraphs.

Software and systems modeling·2026
Same journal

The MDENet education platform: zero-install directed activities for learning MDE.

Software and systems modeling·2026
Same journal

Diagrammatic physical robot models.

Software and systems modeling·2025
Same journal

Extract, model, refine: improved modelling of program verification tools through data enrichment.

Software and systems modeling·2025
Same journal

Using reactive links to propagate changes across engineering models.

Software and systems modeling·2025
Same journal

What makes life for process mining analysts difficult? A reflection of challenges.

Software and systems modeling·2024
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 Experiment Video

Updated: Feb 5, 2026

Methods for Performing Crosses in Setaria viridis, a New Model System for the Grasses
08:35

Methods for Performing Crosses in Setaria viridis, a New Model System for the Grasses

Published on: October 1, 2013

22.3K

The Train Benchmark: cross-technology performance evaluation of continuous model queries.

Gábor Szárnyas1,2,3, Benedek Izsó1, István Ráth1,4

  • 11Department of Measurement and Information Systems, Budapest University of Technology and Economics, Magyar tudósok krt. 2, Budapest, 1117 Hungary.

Software and Systems Modeling
|September 18, 2018
PubMed
Summary
This summary is machine-generated.

This study introduces a benchmark for validating safety-critical system models. It assesses the performance of declarative queries for detecting design flaws in large graph models, crucial for efficient system development.

Keywords:
Graph databasesPerformance benchmarkQuery evaluationRelational databasesSemantic databasesWell-formedness validation

More Related Videos

A Training and Testing System for Performing Vascular Reconstruction In Vitro
09:52

A Training and Testing System for Performing Vascular Reconstruction In Vitro

Published on: October 26, 2019

8.4K
Evaluating the Procedure for Performing Awake Cystometry in a Mouse Model
09:31

Evaluating the Procedure for Performing Awake Cystometry in a Mouse Model

Published on: May 20, 2017

13.4K

Related Experiment Videos

Last Updated: Feb 5, 2026

Methods for Performing Crosses in Setaria viridis, a New Model System for the Grasses
08:35

Methods for Performing Crosses in Setaria viridis, a New Model System for the Grasses

Published on: October 1, 2013

22.3K
A Training and Testing System for Performing Vascular Reconstruction In Vitro
09:52

A Training and Testing System for Performing Vascular Reconstruction In Vitro

Published on: October 26, 2019

8.4K
Evaluating the Procedure for Performing Awake Cystometry in a Mouse Model
09:31

Evaluating the Procedure for Performing Awake Cystometry in a Mouse Model

Published on: May 20, 2017

13.4K

Area of Science:

  • Software Engineering
  • Model-Driven Development
  • Safety-Critical Systems

Background:

  • Model-driven development (MDD) for safety-critical systems requires rigorous model validation to identify design flaws early.
  • Current industrial tools often use complex, imperative code for validation, hindering maintainability and scalability.
  • Increasing model size and complexity challenge the efficiency of existing validation tools.

Purpose of the Study:

  • To present a benchmark for systematically evaluating the scalability of well-formedness constraint validation and revalidation on large graph models.
  • To assess the performance of declarative queries and model transformations for constraint checking and repair operations.
  • To provide a standardized method for comparing different technologies and query engines in the context of model validation.

Main Methods:

  • Development of the 'Train Benchmark' featuring a railway domain metamodel, instance model generator, and well-formedness constraints.
  • Implementation of constraints as declarative queries and fault injection/repair operations as model transformations.
  • Focus on performance metrics including query evaluation time and memory consumption, with emphasis on revalidation efficiency.

Main Results:

  • The benchmark enables systematic assessment of validation and revalidation scalability for large graph models.
  • Demonstrates the applicability of the benchmark across various technologies, including modeling tools, relational, graph, and semantic databases.
  • Provides a foundation for comparing the performance of different query engines for model validation tasks.

Conclusions:

  • Declarative queries offer a more maintainable and potentially scalable approach to well-formedness validation compared to imperative code.
  • The Train Benchmark serves as a valuable open-source resource for researchers and practitioners in safety-critical system development.
  • Performance evaluation using the benchmark is crucial for selecting appropriate technologies for efficient model validation in complex systems.