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

Circadian Rhythms and Gene Regulation02:19

Circadian Rhythms and Gene Regulation

4.2K
The biological clock is involved in many aspects of regulating complex physiology in all animals. It was in 1935 when German zoologists, Hans Kalmus and Erwin Bünning, discovered the existence of circadian rhythm in Drosophila melanogaster. However, the internal molecular mechanisms behind the circadian clock remained a mystery until 1984, when Jeffrey C. Hall, Michael Rosbash, and Michael W. Young discovered the expression of the Per gene oscillating over a 24-hour cycle. In subsequent...
4.2K
Biological Clocks and Seasonal Responses02:45

Biological Clocks and Seasonal Responses

39.3K
The circadian—or biological—clock is an intrinsic, timekeeping, molecular mechanism that allows plants to coordinate physiological activities over 24-hour cycles called circadian rhythms. Photoperiodism is a collective term for the biological responses of plants to variations in the relative lengths of dark and light periods. The period of light-exposure is called the photoperiod.
39.3K
Chronopharmacokinetics: Circadian Rhythms and Influence on Drug Response01:15

Chronopharmacokinetics: Circadian Rhythms and Influence on Drug Response

137
Circadian rhythms are cyclic changes that are crucial in plasma drug concentrations. Various standard circadian parameters, including core body temperature, heart rate, and other cardiovascular factors, directly impact disease states and the therapeutic response to drug therapy.
The time of drug administration is an important factor to consider, as it can influence the toxic dose of a drug. For example, a study conducted by Prins et al. in 1997 examined the effects of the timing of...
137
Pharmacokinetic Models: Overview01:20

Pharmacokinetic Models: Overview

1.2K
Pharmacokinetic models utilize mathematical analysis to achieve a detailed quantitative understanding of a drug's life cycle within the body. They are instrumental in simulating a drug's pharmacokinetic parameters, predicting drug concentrations over time, optimizing dosage regimens, linking concentrations with pharmacologic activity, and estimating potential toxicity.
There are three primary types of models: empirical, compartment, and physiological. Empirical models, with minimal...
1.2K
Model Approaches for Pharmacokinetic Data: Physiological Models01:15

Model Approaches for Pharmacokinetic Data: Physiological Models

124
Physiological models in pharmacokinetics are instrumental in understanding the distribution and elimination of drugs within the body. These models describe the drug concentration within target organs, influenced by factors such as drug uptake, tissue volume, and blood flow. Drug uptake is governed by the partition coefficient, which signifies the drug concentration ratio in tissue to that in the blood. The blood flow rate to a specific tissue is expressed as Qt, and the rate of change in tissue...
124
Pharmacokinetic Models: Comparison and Selection Criterion01:26

Pharmacokinetic Models: Comparison and Selection Criterion

155
Physiological and compartmental models are valuable tools used in studying biological systems. These models rely on differential equations to maintain mass balance within the system, ensuring an accurate representation of the dynamic processes at play.
Physiological models take a detailed approach by considering specific molecular processes. They can predict drug distribution, metabolism, and elimination changes, providing a comprehensive understanding of how drugs interact with the body.
155

You might also read

Related Articles

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

Sort by
Same author

HIV-Related Stigma Assessment Through an Integrated Digital Strategy in Routine Clinical Care.

AIDS patient care and STDs·2026
Same author

Impact of Obstetric Complications in Subjects at Clinical High Risk for Psychosis: A Systematic Review and Meta-Analysis.

Acta psychiatrica Scandinavica·2026
Same author

Circadian rhythm heterogeneity modulates drug response variations in neuroblastoma models.

Cell reports·2026
Same author

Time after time - circadian clocks through the lens of oscillator theory.

FEBS letters·2026
Same author

<i>In vivo</i> insights into irregular voice production as a complex nonlinear system-a case study.

Journal of the Royal Society, Interface·2025
Same author

Exploring nonlinear phenomena in animal vocalizations through oscillator theory.

Philosophical transactions of the Royal Society of London. Series B, Biological sciences·2025

Related Experiment Video

Updated: Sep 22, 2025

A Computational Method to Quantify Fly Circadian Activity
13:05

A Computational Method to Quantify Fly Circadian Activity

Published on: October 28, 2017

6.1K

Mathematical Modeling in Circadian Rhythmicity.

Marta Del Olmo1, Saskia Grabe2, Hanspeter Herzel2

  • 1Institute for Theoretical Biology, Charité and Humboldt Universität zu Berlin, Berlin, Germany. marta.del-olmo@charite.de.

Methods in Molecular Biology (Clifton, N.J.)
|May 24, 2022
PubMed
Summary

This chapter explores self-sustained circadian oscillators using nonlinear dynamics. Mathematical models, like ordinary differential equations, help understand these complex biological systems and guide experimental research.

Keywords:
BifurcationsClocksCoupled oscillatorsEntrainmentFeedback loopsLimit cyclesModelingNonlinearitiesOrdinary differential equationsOscillationsSynchronization

More Related Videos

Recording and Analysis of Circadian Rhythms in Running-wheel Activity in Rodents
05:46

Recording and Analysis of Circadian Rhythms in Running-wheel Activity in Rodents

Published on: January 24, 2013

21.5K
Parallel Measurement of Circadian Clock Gene Expression and Hormone Secretion in Human Primary Cell Cultures
06:53

Parallel Measurement of Circadian Clock Gene Expression and Hormone Secretion in Human Primary Cell Cultures

Published on: November 11, 2016

8.4K

Related Experiment Videos

Last Updated: Sep 22, 2025

A Computational Method to Quantify Fly Circadian Activity
13:05

A Computational Method to Quantify Fly Circadian Activity

Published on: October 28, 2017

6.1K
Recording and Analysis of Circadian Rhythms in Running-wheel Activity in Rodents
05:46

Recording and Analysis of Circadian Rhythms in Running-wheel Activity in Rodents

Published on: January 24, 2013

21.5K
Parallel Measurement of Circadian Clock Gene Expression and Hormone Secretion in Human Primary Cell Cultures
06:53

Parallel Measurement of Circadian Clock Gene Expression and Hormone Secretion in Human Primary Cell Cultures

Published on: November 11, 2016

8.4K

Area of Science:

  • * Chronobiology and Systems Biology
  • * Application of Nonlinear Dynamics Theory

Background:

  • * Circadian clocks are autonomous intracellular systems exhibiting self-sustained oscillations.
  • * The molecular clockwork involves intricate, interlocked feedback loops.
  • * External cues (Zeitgebers) typically influence but are not essential for oscillation.

Purpose of the Study:

  • * To discuss self-sustained circadian oscillators within the framework of nonlinear dynamics.
  • * To outline steps for constructing mathematical models of circadian rhythms.
  • * To explore the synchronization and entrainment of coupled oscillators.

Main Methods:

  • * Utilizing nonlinear dynamics theory to analyze oscillator behavior.
  • * Employing ordinary differential equations for modeling self-sustained oscillations.
  • * Investigating synchronization and entrainment phenomena in coupled oscillator systems.

Main Results:

  • * Mathematical models provide insights into the fundamental components of oscillating systems.
  • * Modeling complex network systems aids in understanding their behavior.
  • * Theoretical predictions from simple models can effectively guide experimental studies.

Conclusions:

  • * Nonlinear dynamics offers a powerful lens for studying circadian clocks.
  • * Mathematical modeling is crucial for dissecting the complexity of biological oscillators.
  • * Simple, theoretically-driven models are valuable for qualitative understanding and experimental direction in chronobiology.