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

65.7K
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...
65.7K
Zygotic Development And Stem Cell Formation01:10

Zygotic Development And Stem Cell Formation

6.4K
The development of all multicellular organisms starts with the fusion of haploid cells called sperm and egg to form a diploid zygote. A zygote is a totipotent cell that can develop into a complete organism. The zygote undergoes cell division or cleavage to form an 8-cell mass. Until this stage, the cells are spherical, loosely attached, and remain totipotent. Totipotent cells are capable of developing both the embryonic and the extraembryonic tissues. However, as they continue to divide, they...
6.4K
Cleavage and Blastulation01:33

Cleavage and Blastulation

49.6K
After a large-single-celled zygote is produced via fertilization, the process of cleavage occurs while zygotes travel through the uterine tube. Cleavage is a mitotic cell division that does not result in growth. With each round of successive cell division, daughter cells get increasingly smaller.
49.6K
Determination01:51

Determination

20.6K
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...
20.6K
Cellular Differentiation00:57

Cellular Differentiation

5.0K
How does a complex organism such as a human develop from a single cell? It all starts from a single fertilized egg which gives rise to a vast array of cell types, such as nerve cells, muscle cells, and epithelial cells that characterize the adult? Throughout development and adulthood, cellular differentiation leads cells to assume their final morphology and physiology. Differentiation is the process by which unspecialized cells become specialized to carry out distinct functions.
A zygote is a...
5.0K
Neurulation01:30

Neurulation

45.0K
Neurulation is the embryological process which forms the precursors of the central nervous system and occurs after gastrulation has established the three primary cell layers of the embryo: ectoderm, mesoderm, and endoderm. In humans, the majority of this system is formed via primary neurulation, in which the central portion of the ectoderm—originally appearing as a flat sheet of cells—folds upwards and inwards, sealing off to form a hollow neural tube. As development proceeds, the...
45.0K

You might also read

Related Articles

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

Sort by
Same author

Aging changes cell mechanics and dynamics associated with cytoplasmic crowding.

PNAS nexus·2026
Same author

AutomataGPT: Transformer-Based Forecasting and Ruleset Inference for Two-Dimensional Cellular Automata.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2026
Same author

Molecular-Scale Interactions at Mineralized Collagen Interfaces Prevent Network Percolation, Preserving Compliance.

ACS nano·2025
Same author

Vimentin intermediate filaments as structural and mechanical coordinators of mesenchymal cells.

Nature cell biology·2025
Same author

High-throughput Screening of the Mechanical Properties of Peptide Assemblies.

ArXiv·2025
Same author

Exploring Nature's Toolbox: The Role of Biopolymers in Sustainable Materials Science.

Advanced materials (Deerfield Beach, Fla.)·2025
Same journal

Spatio-DARLIN enables robust and efficient in situ lineage tracing in mice at single-cell resolution.

Nature methods·2026
Same journal

EasyGrid: a versatile platform for automated cryo-EM sample preparation and quality control.

Nature methods·2026
Same journal

Cloud-based microscope enables live neuroimaging for 24 h and beyond with worldwide access.

Nature methods·2026
Same journal

Deep molecular profiling in three dimensions.

Nature methods·2026
Same journal

3D pathology-guided microdissection.

Nature methods·2026
Same journal

Challenges and recommendations in establishing national human diversity genomic projects.

Nature methods·2026
See all related articles

Related Experiment Video

Updated: Jan 8, 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

6.9K

MultiCell: geometric learning in multicellular development.

Haiqian Yang1, George Roy2, Anh Q Nguyen3

  • 1Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA. hqyang@mit.edu.

Nature Methods
|December 16, 2025
PubMed
Summary
This summary is machine-generated.

Researchers developed MultiCell, a geometric deep learning tool, to predict cell behaviors during development. This method accurately captures cell interactions, advancing our understanding of embryogenesis and morphodynamics.

More Related Videos

Patterning the Geometry of Human Embryonic Stem Cell Colonies on Compliant Substrates to Control Tissue-Level Mechanics
10:04

Patterning the Geometry of Human Embryonic Stem Cell Colonies on Compliant Substrates to Control Tissue-Level Mechanics

Published on: September 28, 2019

8.8K
Imaging and Analysis of Tissue Orientation and Growth Dynamics in the Developing Drosophila Epithelia During Pupal Stages
08:25

Imaging and Analysis of Tissue Orientation and Growth Dynamics in the Developing Drosophila Epithelia During Pupal Stages

Published on: June 2, 2020

9.9K

Related Experiment Videos

Last Updated: Jan 8, 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

6.9K
Patterning the Geometry of Human Embryonic Stem Cell Colonies on Compliant Substrates to Control Tissue-Level Mechanics
10:04

Patterning the Geometry of Human Embryonic Stem Cell Colonies on Compliant Substrates to Control Tissue-Level Mechanics

Published on: September 28, 2019

8.8K
Imaging and Analysis of Tissue Orientation and Growth Dynamics in the Developing Drosophila Epithelia During Pupal Stages
08:25

Imaging and Analysis of Tissue Orientation and Growth Dynamics in the Developing Drosophila Epithelia During Pupal Stages

Published on: June 2, 2020

9.9K

Area of Science:

  • Developmental Biology
  • Computational Biology
  • Biophysics

Background:

  • Understanding cell self-organization during embryogenesis is crucial but challenging.
  • Predicting individual cell behavior in living tissues over time remains a significant hurdle.
  • Existing methods struggle to capture complex intercellular interactions.

Purpose of the Study:

  • To present MultiCell, a novel geometric deep learning method for analyzing multicellular dynamics.
  • To represent complex multicellular data using a unified graph structure.
  • To predict single-cell behaviors during developmental processes with high resolution.

Main Methods:

  • Developed MultiCell, a geometric deep learning framework.
  • Utilized a unified graph data structure to represent cellular interactions and cell junction networks.
  • Applied the method to four-dimensional morphological sequence alignment.
  • Employed neural activation maps and model ablation studies.

Main Results:

  • MultiCell accurately captures convoluted interactions among cells.
  • Achieved interpretable 4D morphological sequence alignment.
  • Successfully predicted single-cell behaviors during Drosophila embryogenesis at single-cell resolution.
  • Demonstrated the essential roles of cell geometry and junction networks in predicting cell behaviors.

Conclusions:

  • MultiCell provides a data-driven approach for quantitative studies of dynamic multicellular processes.
  • The method enables precise prediction of cell behaviors during development.
  • This work offers a pathway toward a unified morphodynamic atlas with single-cell precision.