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

Pharmacokinetic Models: Overview01:20

Pharmacokinetic Models: Overview

1.3K
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...
1.3K
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

115
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
115
Model Approaches for Pharmacokinetic Data: Physiological Models01:15

Model Approaches for Pharmacokinetic Data: Physiological Models

133
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...
133
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

99
Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
99

You might also read

Related Articles

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

Sort by
Same author

Integrating mechanistic models to decode the GnRH pulse generator in female mice.

Journal of molecular endocrinology·2026
Same author

The role of amygdala GABA neurons in controlling stress and reproduction in female mice.

Nature communications·2026
Same author

The Concise Guide to PHARMACOLOGY 2025/26: G protein-coupled receptors.

British journal of pharmacology·2025
Same author

Placental growth plays a key role in the link between maternal glucose levels in pregnancy and risk of preeclampsia.

medRxiv : the preprint server for health sciences·2025
Same author

Modelling Follicular Growth During Ovarian Stimulation Using Agent-based Artificial Intelligence.

The Journal of clinical endocrinology and metabolism·2025
Same author

Heterogeneous efflux pump expression underpins phenotypic resistance to antimicrobial peptides.

eLife·2025

Related Experiment Video

Updated: Oct 5, 2025

Establishment of Rat Models Mimicking Gender-affirming Hormone Therapies
06:24

Establishment of Rat Models Mimicking Gender-affirming Hormone Therapies

Published on: January 10, 2025

965

Mathematical models in GnRH research.

Margaritis Voliotis1, Zoe Plain1, Xiao Feng Li2

  • 1Department of Mathematics and Living Systems Institute, College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, UK.

Journal of Neuroendocrinology
|January 26, 2022
PubMed
Summary
This summary is machine-generated.

Mathematical modeling advances reproductive neuroendocrine research by detailing Gonadotropin-releasing hormone (GnRH) neuron function, pulsatile secretion, and pituitary signaling. These models offer new insights into GnRH dynamics and reproductive system complexities.

Keywords:
GnRHbiophysical modellingmathematical modelling

More Related Videos

Dual Somatic Recordings from Gonadotropin-Releasing Hormone GnRH Neurons Identified by Green Fluorescent Protein GFP in Hypothalamic Slices
09:30

Dual Somatic Recordings from Gonadotropin-Releasing Hormone GnRH Neurons Identified by Green Fluorescent Protein GFP in Hypothalamic Slices

Published on: February 23, 2010

22.4K
Ex Vivo Release of Calcitonin Gene-Related Peptide from the Trigeminovascular System in Rodents
08:39

Ex Vivo Release of Calcitonin Gene-Related Peptide from the Trigeminovascular System in Rodents

Published on: May 16, 2022

2.6K

Related Experiment Videos

Last Updated: Oct 5, 2025

Establishment of Rat Models Mimicking Gender-affirming Hormone Therapies
06:24

Establishment of Rat Models Mimicking Gender-affirming Hormone Therapies

Published on: January 10, 2025

965
Dual Somatic Recordings from Gonadotropin-Releasing Hormone GnRH Neurons Identified by Green Fluorescent Protein GFP in Hypothalamic Slices
09:30

Dual Somatic Recordings from Gonadotropin-Releasing Hormone GnRH Neurons Identified by Green Fluorescent Protein GFP in Hypothalamic Slices

Published on: February 23, 2010

22.4K
Ex Vivo Release of Calcitonin Gene-Related Peptide from the Trigeminovascular System in Rodents
08:39

Ex Vivo Release of Calcitonin Gene-Related Peptide from the Trigeminovascular System in Rodents

Published on: May 16, 2022

2.6K

Area of Science:

  • Neuroscience
  • Mathematical Biology
  • Reproductive Endocrinology

Background:

  • Mathematical modeling is crucial for quantitative analysis in biosciences.
  • Over 20 years, models have explored Gonadotropin-releasing hormone (GnRH) neuron physiology and signaling.
  • Understanding complex biological systems relies on integrated data and model predictions.

Purpose of the Study:

  • To review the impact of mathematical modeling on Gonadotropin-releasing hormone (GnRH) research.
  • To highlight how models have advanced our comprehension of GnRH neuron function and secretion.
  • To discuss the predictive power of models in reproductive neuroendocrine system research.

Main Methods:

  • Literature review of mathematical modeling applications in GnRH research.
  • Analysis of model contributions to understanding GnRH neuron bursting behavior.
  • Examination of models elucidating GnRH signaling pathways to the pituitary.

Main Results:

  • Mathematical models have elucidated GnRH neuron physiology and pulsatile secretion mechanisms.
  • Models have provided novel hypotheses on kisspeptin neuron roles in GnRH pulsatility.
  • Studies show models help decode GnRH signals within pituitary biochemical networks.

Conclusions:

  • Mathematical modeling has significantly impacted GnRH research over the past two decades.
  • Models offer valuable predictions and hypotheses, driving experimental design and discovery.
  • Future advancements in experimental technologies will enhance the role of modeling in reproductive neuroendocrine research.