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

Gastrulation01:56

Gastrulation

Gastrulation establishes the three primary tissues of an embryo: the ectoderm, mesoderm, and endoderm. This developmental process relies on a series of intricate cellular movements, which in humans transforms a flat, “bilaminar disc” composed of two cell sheets into a three-tiered structure. In the resulting embryo, the endoderm serves as the bottom layer, and stacked directly above it is the intermediate mesoderm, and then the uppermost ectoderm. Respectively, these tissue strata will form...
Determination01:51

Determination

During embryogenesis, cells become progressively committed to different fates through a two-step process: specification followed by determination. Specification is demonstrated by removing a segment of an early embryo, “neutrally” culturing the tissue in vitro—for example, in a petri dish with simple medium—and then observing the derivatives. If the cultured region gives rise to cell types that it would normally generate in the embryo, this means that it is specified. In contrast, determination...
Morphogenesis02:19

Morphogenesis

Plant morphogenesis—the development of a plant’s form and structure—involves several overlapping developmental processes, including growth and cell differentiation. Precursor cells differentiate into specific cell types, which are organized into the tissues and organ systems that make up the functional plant.

You might also read

Related Articles

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

Sort by
Same author

Multilayer Network Analysis of European Regional Flows.

Entropy (Basel, Switzerland)·2025
Same author

Egosyntonicity and emotion regulation: a probabilistic model of valence dynamics.

Royal Society open science·2025
Same author

Author Correction: Tracing two decades of carbon emissions using a network approach.

Scientific reports·2024
Same author

Tracing two decades of carbon emissions using a network approach.

Scientific reports·2024
Same author

A machine learning approach to assess Sustainable Development Goals food performances: The Italian case.

PloS one·2024
Same author

A multi-modal machine learning approach to detect extreme rainfall events in Sicily.

Scientific reports·2023
Same journal

Analysis of strength degradation of coal and rock masses and stability of mined areas under long term immersion environment.

PloS one·2026
Same journal

Biogenic Silver-Selenium nanocomposite with anticancer activity and potent efficacy against vancomycin-resistant Staphylococcus aureus.

PloS one·2026
Same journal

Preparation and physicochemical characterization of a biodegradable chitosan/carboxymethyl cellulose hydrogel synthesized in NaOH/urea medium.

PloS one·2026
Same journal

Action-guilt, survivor-guilt, and depression in combat-related PTSD.

PloS one·2026
Same journal

Explainable machine learning for predicting activities of daily living at discharge in stroke patients: A retrospective study using SHAP interpretability.

PloS one·2026
Same journal

Deep learning based two-way feature depiction model for brain tumor detection.

PloS one·2026
See all related articles

Related Experiment Video

Updated: May 7, 2026

Mapping the Emergent Spatial Organization of Mammalian Cells using Micropatterns and Quantitative Imaging
09:56

Mapping the Emergent Spatial Organization of Mammalian Cells using Micropatterns and Quantitative Imaging

Published on: April 30, 2019

Recurrence methods for the identification of morphogenetic patterns.

Angelo Facchini1, Chiara Mocenni

  • 1Enel Foundation, Rome, Italy.

Plos One
|September 26, 2013
PubMed
Summary
This summary is machine-generated.

This study uses recurrence quantification analysis to characterize spatial patterns in nonlinear systems. Recurrence measures effectively identify pattern parameters and outperform Fourier transforms, even with added noise.

More Related Videos

Analysis of Cell Differentiation, Morphogenesis, and Patterning During Chicken Embryogenesis Using the Soaked-Bead Assay
06:49

Analysis of Cell Differentiation, Morphogenesis, and Patterning During Chicken Embryogenesis Using the Soaked-Bead Assay

Published on: January 12, 2022

Tracking Morphogenetic Tissue Deformations in the Early Chick Embryo
08:19

Tracking Morphogenetic Tissue Deformations in the Early Chick Embryo

Published on: October 17, 2011

Related Experiment Videos

Last Updated: May 7, 2026

Mapping the Emergent Spatial Organization of Mammalian Cells using Micropatterns and Quantitative Imaging
09:56

Mapping the Emergent Spatial Organization of Mammalian Cells using Micropatterns and Quantitative Imaging

Published on: April 30, 2019

Analysis of Cell Differentiation, Morphogenesis, and Patterning During Chicken Embryogenesis Using the Soaked-Bead Assay
06:49

Analysis of Cell Differentiation, Morphogenesis, and Patterning During Chicken Embryogenesis Using the Soaked-Bead Assay

Published on: January 12, 2022

Tracking Morphogenetic Tissue Deformations in the Early Chick Embryo
08:19

Tracking Morphogenetic Tissue Deformations in the Early Chick Embryo

Published on: October 17, 2011

Area of Science:

  • Nonlinear dynamics
  • Pattern formation
  • Biophysics

Background:

  • Spatial patterns are crucial in biological development (morphogenesis).
  • Understanding the parameters controlling pattern formation in nonlinear systems is challenging.
  • Turing patterns are a key model for studying reaction-diffusion based pattern formation.

Purpose of the Study:

  • To identify parameters governing spatial pattern formation in nonlinear 2D systems.
  • To characterize morphogenetic Turing patterns using novel quantitative measures.
  • To compare the efficacy of recurrence quantification analysis with traditional methods.

Main Methods:

  • Numerical experiments on a prototypical model for morphogenetic Turing patterns.
  • Application of Generalized Recurrence Quantification analysis (RQ) measures.
  • Systematic variation of spatial frequency and pattern shape.
  • Comparison with the two-dimensional Fourier transform.
  • Robustness testing with added noise.

Main Results:

  • Recurrence measures (Determinism, Recurrence Entropy) and line length distributions characterize patterns.
  • Power law decay relationships were identified between pattern features and model parameters.
  • Recurrence indicators showed superior performance over Fourier transforms in linking parameters to spatial frequency.
  • The methods demonstrated robustness against varying levels of noise.

Conclusions:

  • Generalized Recurrence Quantification analysis is a powerful tool for characterizing spatial patterns in nonlinear systems.
  • Recurrence measures provide a more reliable link to pattern-forming parameters than Fourier analysis.
  • This approach offers a robust method for analyzing complex pattern formation, applicable even in noisy environments.