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

Contact-dependent Signaling01:19

Contact-dependent Signaling

46.8K
Contact-dependent signaling, as the name suggests, requires that communicating cells be in direct contact with each other. This is achieved either through receptor-ligand interactions or by specialized cytoplasmic channels that allow the flow of small molecules between cells. In animal cells, channels called gap junctions facilitate contact-dependent signaling in certain tissues, whereas, plasmodesmata perform a similar function in plants.
Gap Junctions
In animal cells, gap junctions are formed...
46.8K
Overview of Cell-Matrix Interactions01:24

Overview of Cell-Matrix Interactions

8.9K
The extracellular matrix or ECM holds cells together to form a tissue and allows the cells within the tissue to communicate. ECM comprises proteins such as fibronectin, collagen, laminin, etc. The most abundant protein in this space is collagen. Collagen fibers are interwoven with carbohydrate-containing protein molecules called proteoglycans. ECM allows cell migration and provides a structural scaffold at cell adhesion that anchors the cell when the extracellular matrix proteins interact with...
8.9K
Modeling with Differential Equations01:25

Modeling with Differential Equations

20
Population dynamics can be described mathematically by considering the population size P(t) as a function of time. The rate of change of the population is then represented by the derivative of P(t). A simple assumption is that the rate of growth is proportional to the size of the population itself. This leads to an exponential growth model, where the population increases rapidly without bound. While this is a useful first approximation, it does not reflect realistic long-term...
20
Cell Migration01:19

Cell Migration

6.4K
Cell migration is a process by which the cells move from one location to another, playing an essential role in embryological development, repair and regeneration, immune response, and metastasis. Cells migrate in response to chemical or mechanical signals generated by specific organs or tissues. The overall mechanism includes three steps - polarization, protrusion, and release. Polarization involves the formation of a distinct cell front and rear, which determines the direction of movement.
6.4K
Cell Migration01:09

Cell Migration

18.6K
Cell migration, the process by which cells move from one location to another, is essential for the proper development and viability of organisms throughout their life. When cells are not able to migrate properly to their ordained locations, various disorders may occur. For example, disruption in cell migration causes chronic inflammatory diseases such as arthritis.
18.6K
Cell Motility through Blebbing01:16

Cell Motility through Blebbing

2.4K
Blebs are a type of membrane protrusion formed by the internal hydrostatic pressure of the cytoplasm. Blebs are observed in several cell types, including fibroblasts, immune cells, and single-celled organisms like the amoeba. The primary function of blebs is cell locomotion and apoptosis, but they are also found during necrosis and cell division. The life cycle of a bleb comprises an initiation phase followed by the expansion and retraction phases.
Blebbing Through the Matrix
In multicellular...
2.4K

You might also read

Related Articles

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

Sort by
Same author

Injury prediction in elite women's football: an integrative machine learning-based decision-support framework.

NPJ digital medicine·2026
Same author

Wastewater-based sequencing of respiratory syncytial virus to investigate lineage dynamics and antigenic site mutations: a retrospective genomic epidemiology study.

The Lancet. Microbe·2026
Same author

Longitudinal spatial neutrophil profiling during ACT in murine melanoma reveals distinct lymph node infiltration patterns.

NPJ systems biology and applications·2026
Same author

Data-driven model reveals increased stability of CAG-expanded huntingtin RNA due to MID1 binding.

PLoS computational biology·2026
Same author

Homing pigeon navigation relies on superparamagnetic macrophages under overcast conditions.

Science (New York, N.Y.)·2026
Same author

Suggested experimental design and computational modeling to infer single-cell lipid dynamics from a single destructive measurement.

iScience·2026

Related Experiment Video

Updated: Jan 17, 2026

Sandwich-like Microenvironments to Harness Cell/Material Interactions
06:50

Sandwich-like Microenvironments to Harness Cell/Material Interactions

Published on: August 4, 2015

8.0K

A dynamic model for Waddington's landscape accounting for cell-to-cell communication.

Simon Merkt1, Lara Fuhrmann2, Erika Dudkin3

  • 1Life and Medical Sciences (LIMES), University of Bonn, Carl-Troll-Str. 31, Bonn, 53115, North Rhine-Westphalia, Germany; Bonn Center for Mathematical Life Sciences, University of Bonn, Endenicher Allee 64, Bonn, 53115, North Rhine-Westphalia, Germany.

Mathematical Biosciences
|September 21, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces a new mathematical model extending Waddington's landscape to include cell-to-cell communication, crucial for understanding biological development and recovery processes.

Keywords:
Cell-to-cell communicationDendritic cell activationParameter estimationPopulation dynamicsSingle-cell transcriptomics dataStem cell regenerationWaddington’s landscape

More Related Videos

Isolation and Time-Lapse Imaging of Primary Mouse Embryonic Palatal Mesenchyme Cells to Analyze Collective Movement Attributes
07:13

Isolation and Time-Lapse Imaging of Primary Mouse Embryonic Palatal Mesenchyme Cells to Analyze Collective Movement Attributes

Published on: February 13, 2021

2.6K
Finite Element Modelling of a Cellular Electric Microenvironment
08:23

Finite Element Modelling of a Cellular Electric Microenvironment

Published on: May 18, 2021

4.0K

Related Experiment Videos

Last Updated: Jan 17, 2026

Sandwich-like Microenvironments to Harness Cell/Material Interactions
06:50

Sandwich-like Microenvironments to Harness Cell/Material Interactions

Published on: August 4, 2015

8.0K
Isolation and Time-Lapse Imaging of Primary Mouse Embryonic Palatal Mesenchyme Cells to Analyze Collective Movement Attributes
07:13

Isolation and Time-Lapse Imaging of Primary Mouse Embryonic Palatal Mesenchyme Cells to Analyze Collective Movement Attributes

Published on: February 13, 2021

2.6K
Finite Element Modelling of a Cellular Electric Microenvironment
08:23

Finite Element Modelling of a Cellular Electric Microenvironment

Published on: May 18, 2021

4.0K

Area of Science:

  • Developmental Biology
  • Mathematical Modeling
  • Systems Biology

Background:

  • Waddington's landscape is a conceptual model for development.
  • Existing mathematical models often neglect cell-to-cell communication.
  • Cellular communication significantly influences cell decisions and population dynamics.

Purpose of the Study:

  • To develop a dynamical model extending Waddington's landscape.
  • To incorporate cell-to-cell communication into developmental models.
  • To analyze biological recovery processes using the new model.

Main Methods:

  • Developed a coupled system of partial and ordinary differential equations.
  • Modeled cell density and ligand concentrations.
  • Validated the model using single-cell transcriptomics data.

Main Results:

  • Cell-to-cell communication is essential for accurate modeling of biological recovery.
  • The model successfully depicts stem cell regeneration in the intestine.
  • The model captures immune cell responses to stimulation.

Conclusions:

  • Incorporating cell-to-cell communication enhances mathematical models of biological development.
  • This approach provides deeper insights into tissue regeneration and immune responses.
  • The model offers new ways to predict biological recovery and cell activation dynamics.