Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Determining the Plane of Cell Division

Determining the Plane of Cell Division

Positioning the cell division plane is a critical step during development and cell differentiation, particularly during mitosis when the plane is essential for determining the size of the two daughter cells. The cell division plane is perpendicular to the plane of chromosome segregation, but different types of organisms have different cell division mechanisms to suit their morphology and function.
Animal cells
In animal cells, the cleavage furrow forms along the plane of cell division...

You might also read

Related Articles

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

Sort by

Same author

Locally synthesized glycyl aminoacyl-tRNA synthetase is important for local translation in neurons.

Life science alliance·2026

Same author

A likelihood-based Bayesian inference framework for the calibration of and selection between stochastic velocity-jump models.

Journal of the Royal Society, Interface·2026

Same author

Deep3DSIM: Super-resolution imaging of thick tissue using 3D structured illumination with adaptive optics.

eLife·2025

Same author

Eomes directs the formation of spatially and functionally diverse extraembryonic hematovascular tissues.

Developmental cell·2025

Same author

Destabilisation of bam transcripts terminates the mitotic phase of Drosophila female germline differentiation.

Development (Cambridge, England)·2025

Same author

Imp/IGF2BP and Syp/SYNCRIP temporal RNA interactomes uncover combinatorial networks of regulators of <i>Drosophila</i> brain development.

Science advances·2025

Same journal

The exquisite mechanics of a tsetse bite.

eLife·2026

Same journal

Distinct involvements of the subthalamic nucleus subpopulations in reward-biased decision-making in monkeys.

eLife·2026

Same journal

Pink1-mediated mitophagy in the endothelium releases proteins encoded by mitochondrial DNA and activates neutrophil responses during inflammation.

eLife·2026

Same journal

Restraint of melanoma progression by cells in the local skin environment.

eLife·2026

Same journal

Brawn before bite in endemic Asian eutherian mammals after the end-Cretaceous extinction.

eLife·2026

Same journal

Experimental evolution to thermal stress indicates climate resilience in a cosmopolitan arthropod.

eLife·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Dec 21, 2025

Analysis of Multidimensional Microscopy Data Using Cell-ACDC

Analysis of Multidimensional Microscopy Data Using Cell-ACDC

Published on: November 7, 2025

CytoCensus, mapping cell identity and division in tissues and organs using machine learning.

Martin Hailstone¹, Dominic Waithe², Tamsin J Samuels¹

¹Department of Biochemistry, University of Oxford, Oxford, United Kingdom.

|May 20, 2020

Summary

This summary is machine-generated.

CytoCensus is a new tool for automated cell counting in complex tissues. It uses machine learning for accurate and fast 3D cell detection, aiding developmental biology research.

Keywords:

3D cell detection 4D image analysis D. melanogaster cell biology developmental biology ex vivo culture live imaging mouse neural stem cells zebrafish

More Related Videos

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

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

Published on: April 30, 2019

Morphology-Based Distinction Between Healthy and Pathological Cells Utilizing Fourier Transforms and Self-Organizing Maps

Morphology-Based Distinction Between Healthy and Pathological Cells Utilizing Fourier Transforms and Self-Organizing Maps

Published on: October 28, 2018

Related Experiment Videos

Last Updated: Dec 21, 2025

Analysis of Multidimensional Microscopy Data Using Cell-ACDC

Analysis of Multidimensional Microscopy Data Using Cell-ACDC

Published on: November 7, 2025

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

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

Published on: April 30, 2019

Morphology-Based Distinction Between Healthy and Pathological Cells Utilizing Fourier Transforms and Self-Organizing Maps

Morphology-Based Distinction Between Healthy and Pathological Cells Utilizing Fourier Transforms and Self-Organizing Maps

Published on: October 28, 2018

Area of Science:

Cell and developmental biology
Bioimage analysis
Computational biology

Background:

Automated cell identification and quantitation in complex tissues is a significant challenge.
Existing methods struggle with ill-defined cell boundaries and 3D structures.

Purpose of the Study:

To develop an automated, accurate, and fast method for cell detection and quantitation in complex multilayered tissues.
To provide a user-friendly tool for analyzing challenging biological datasets.

Main Methods:

Development of CytoCensus, a supervised machine learning implementation.
Utilizing 2D 'point-and-click' user training for 3D cell detection.
Testing on challenging datasets with ill-defined cell boundaries.

Main Results:

CytoCensus outperforms existing freely available image analysis software in accuracy and speed.
Successfully used for counting stem cells and quantifying cell divisions in Drosophila larval brains.
Demonstrated utility in analyzing 3D organization in Zebrafish retinal organoids and mouse embryos.

Conclusions:

CytoCensus enables straightforward and robust automated analysis of developmental phenotypes in complex tissues.
The tool has broad applicability across various model organisms and tissue types.
Facilitates advanced research in developmental biology and cell biology.