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

You might also read

Related Articles

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

Sort by
Same author

Active and probe-free intracellular rheology via phase-sensitive thermoviscous flows.

PNAS nexus·2026
Same author

Keratins coordinate tissue spreading by balancing spreading forces with tissue material properties.

Nature communications·2026
Same author

Multiple Notch ligands in the synchronization of the segmentation clock.

Physical review. E·2025
Same author

Decoding zebrafish oogenesis: From primordial germ cell development to fertilization.

Seminars in cell & developmental biology·2025
Same author

Unified mass imaging maps the lipidome of vertebrate development.

Nature methods·2025
Same author

A role for Myosin in triggering and executing amnioserosa cell delaminations during dorsal closure.

Scientific reports·2025
Same journal

Genetic origins and constraints of evolutionary innovation.

Nature reviews. Genetics·2026
Same journal

Single-cell four-omics with CHARM.

Nature reviews. Genetics·2026
Same journal

Molecular integration of seasonal temperature signals in flowering time control.

Nature reviews. Genetics·2026
Same journal

RBPscan measures protein-RNA interactions in living cells.

Nature reviews. Genetics·2026
Same journal

Revisiting retinal and macular degeneration in the genomics era.

Nature reviews. Genetics·2026
Same journal

How evolution builds three morphs from one genome.

Nature reviews. Genetics·2026
See all related articles

Related Experiment Video

Updated: Jun 21, 2026

Tracking and Quantifying Developmental Processes in C. elegans Using Open-source Tools
10:41

Tracking and Quantifying Developmental Processes in C. elegans Using Open-source Tools

Published on: December 16, 2015

Quantitative approaches in developmental biology.

Andrew C Oates1, Nicole Gorfinkiel, Marcos González-Gaitán

  • 1Max Planck Institute of Molecular Cell Biology and Genetics, D-01307 Dresden, Germany. oates@mpi-cbg.de

Nature Reviews. Genetics
|July 9, 2009
PubMed
Summary
This summary is machine-generated.

Mathematical modeling and quantitative imaging are essential for understanding complex embryonic development. This approach integrates molecular, cellular, and tissue-level data to connect gene activity with organism morphology.

More Related Videos

A Comparative Approach for Quantitative Cell Counting Studies in Widely Different Mammalian Brains
07:14

A Comparative Approach for Quantitative Cell Counting Studies in Widely Different Mammalian Brains

Published on: January 16, 2026

Why Quantification Matters: Characterization of Phenotypes at the Drosophila Larval Neuromuscular Junction
10:41

Why Quantification Matters: Characterization of Phenotypes at the Drosophila Larval Neuromuscular Junction

Published on: May 12, 2016

Related Experiment Videos

Last Updated: Jun 21, 2026

Tracking and Quantifying Developmental Processes in C. elegans Using Open-source Tools
10:41

Tracking and Quantifying Developmental Processes in C. elegans Using Open-source Tools

Published on: December 16, 2015

A Comparative Approach for Quantitative Cell Counting Studies in Widely Different Mammalian Brains
07:14

A Comparative Approach for Quantitative Cell Counting Studies in Widely Different Mammalian Brains

Published on: January 16, 2026

Why Quantification Matters: Characterization of Phenotypes at the Drosophila Larval Neuromuscular Junction
10:41

Why Quantification Matters: Characterization of Phenotypes at the Drosophila Larval Neuromuscular Junction

Published on: May 12, 2016

Area of Science:

  • Developmental biology
  • Systems biology
  • Biophysics

Background:

  • Embryonic development involves complex, coordinated processes of cell communication, patterning, migration, and differentiation.
  • Understanding these self-organizing phenomena requires integrating information across multiple biological scales.

Purpose of the Study:

  • To highlight the necessity of quantitative mathematical frameworks for understanding embryonic development.
  • To emphasize the role of dynamic imaging in advancing developmental biology research.
  • To demonstrate how mathematical modeling bridges molecular activities with organismal morphology.

Main Methods:

  • Utilizing quantitative mathematical modeling to formulate and test hypotheses.
  • Employing dynamic imaging techniques at molecular, cellular, and tissue levels.
  • Integrating multi-scale biological data through computational approaches.

Main Results:

  • Mathematical modeling provides a framework to connect molecular regulation with macroscopic morphological changes.
  • Quantitative imaging advances the ability to gather high-resolution data during embryonic development.
  • The integration of theory and experiment is crucial for deciphering self-organizing developmental processes.

Conclusions:

  • Quantitative approaches, particularly mathematical modeling, are indispensable for a comprehensive understanding of embryonic development.
  • The synergy between advanced imaging and theoretical modeling drives progress in developmental biology.
  • This integrated approach facilitates the study of how cellular behaviors lead to organismal form.