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Updated: Apr 9, 2026

Tracking and Quantifying Developmental Processes in C. elegans Using Open-source Tools
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Quantitative multivariate analysis of dynamic multicellular morphogenic trajectories.

Douglas E White1, Jonathan B Sylvester, Thomas J Levario

  • 1The Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, USA. todd.mcdevitt@gladstone.ucsf.edu melissa.kemp@bme.gatech.edu.

Integrative Biology : Quantitative Biosciences From Nano to Macro
|June 23, 2015
PubMed
Summary
This summary is machine-generated.

We developed a new computational pipeline to analyze cell behavior during tissue development. This method allows quantitative comparison of complex biological patterns across different systems, advancing developmental biology research.

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Area of Science:

  • Cell Biology
  • Developmental Biology
  • Systems Biology

Background:

  • Understanding tissue morphogenesis is key to developmental biology and engineering multicellular systems.
  • Embryonic stem cell (ESC) aggregates offer experimental platforms, but analyzing emergent spatial patterns is challenging.
  • Quantitative analysis and comparison of computational models with experimental data are difficult.

Purpose of the Study:

  • To develop a quantitative method for analyzing and comparing morphogenic patterns across diverse biological systems.
  • To enable robust comparison between computational simulations and experimental data in developmental biology.
  • To identify mechanisms driving spatial pattern formation in multicellular systems.

Main Methods:

  • Developed a portable pattern recognition pipeline.
  • Converted cellular images into networks for feature extraction using network analysis.
  • Generated morphogenic trajectories for quantitative description.

Main Results:

  • Enabled quantitative description and comparison of morphogenic trajectories across computational models, ESC differentiation, and fish gastrulation.
  • Identified novel spatio-temporal features during embryo gastrulation.
  • Elucidated a paracrine mechanism explaining size-dependent kinetic differences in ESC aggregates.

Conclusions:

  • The developed pipeline provides a powerful tool for quantitative analysis of morphogenic patterns.
  • This methodology facilitates cross-system comparisons, advancing our understanding of emergent properties in multicellular biology.
  • The findings offer insights into mechanisms regulating tissue development and stem cell differentiation.