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 Experiment Videos

Estimation of cell cycle parameters from double labeling experiments.

E O Voit1, H J Anton

  • 1Zoologisches Institut der Universität zu Köln, Bundesrepublik Deutschland.

Journal of Theoretical Biology
|April 21, 1988
PubMed
Summary
This summary is machine-generated.

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

Plasmodium knowlesi: a superb in vivo nonhuman primate model of antigenic variation in malaria.

Parasitology·2017
Same author

The neurochemical mobile with non-linear interaction matrix: an exploratory computational model.

Pharmacopsychiatry·2013
Same author

Mesoscopic models of neurotransmission as intermediates between disease simulators and tools for discovering design principles.

Pharmacopsychiatry·2012
Same author

Effects of dopamine and glutamate on synaptic plasticity: a computational modeling approach for drug abuse as comorbidity in mood disorders.

Pharmacopsychiatry·2011
Same author

So, you want to be a systems biologist? Determinants for creating graduate curricula in systems biology.

IET systems biology·2011
Same author

Computational modeling of synaptic neurotransmission as a tool for assessing dopamine hypotheses of schizophrenia.

Pharmacopsychiatry·2010
Same journal

Evolution of quantitative traits: exploring the ecological, social and genetic bases of adaptive polymorphism.

Journal of theoretical biology·2026
Same journal

The male-biased sex ratio in humans and its role in the transition from promiscuity to pair bonding.

Journal of theoretical biology·2026
Same journal

Quantifying the counter-intuitive effects of vaccination by coupling the transmission dynamics of COVID-19 and the evolution of human behaviors.

Journal of theoretical biology·2026
Same journal

An integrative model of FGF2-induced signaling and muscle cell proliferation.

Journal of theoretical biology·2026
Same journal

A hybrid reaction-diffusion and mechanical stimulus model for mandibular bone remodeling under chewing and vibratory loading.

Journal of theoretical biology·2026
Same journal

Integrated tick management strategies in fragmented peridomestic environments.

Journal of theoretical biology·2026
See all related articles

This study presents a new method to estimate cell cycle parameters, doubling time (T) and S-phase length (S), in cell populations with varied cycle durations. The approach simplifies calculations without needing explicit distribution data.

Area of Science:

  • Cell biology
  • Biophysics
  • Mathematical modeling

Background:

  • Estimating cell proliferation parameters like doubling time (T) and S-phase length (S) is crucial in cell biology.
  • Current methods often assume either stationary or exponentially growing cell populations with uniform cell cycle durations.
  • These assumptions limit the accurate assessment of T and S in more complex, heterogeneous cell populations.

Purpose of the Study:

  • To develop a generalized method for calculating cell cycle parameters (T and S) in cell populations with arbitrarily distributed cycle durations.
  • To demonstrate that this generalized method does not require explicit knowledge of the cell cycle duration frequency distribution.
  • To establish relationships between estimates from the general model and those from simplified stationary or exponential growth models.

Related Experiment Videos

Main Methods:

  • Utilizing double labeling with radioactive thymidine to label distinct cell populations.
  • Analyzing the numbers of unlabeled, singly labeled, and doubly labeled nuclei.
  • Applying mathematical calculations to derive T and S for populations with varied cycle duration distributions.

Main Results:

  • The estimation of T and S is independent of the explicit frequency distribution of cell cycle durations.
  • Equivalent estimates for T and S are achieved for both arbitrarily distributed and uniformly distributed cell cycle durations in growing populations without losses.
  • For low labeling indices, the generalized model's S-phase estimates converge to stationary population S-phase lengths, and T estimates approach stationary generation times multiplied by ln(2).

Conclusions:

  • The generalized method provides accurate estimations of cell cycle parameters (T and S) for diverse cell populations, including those with heterogeneous cycle durations.
  • This approach simplifies the analysis of cell proliferation dynamics, reducing the need for complex computational efforts or assumptions of uniform cell cycles.
  • The derived relationships allow for the reinterpretation of existing data obtained under stationarity assumptions, enhancing the understanding of cell proliferation in various biological contexts.