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

Distributions to Estimate Population Parameter01:26

Distributions to Estimate Population Parameter

5.1K
The accurate values of population parameters such as population proportion, population mean, and population standard deviation (or variance) are usually unknown. These are fixed values that can only be estimated from the data collected from the samples. The estimates of each of these parameters are sample proportion, the sample mean, and sample standard deviation (or variance). To obtain the values of these sample statistics, data are required that have particular distribution and central...
5.1K
One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation01:24

One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation

1.1K
This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
On...
1.1K
Kinetic Energy00:23

Kinetic Energy

43.4K
Kinetic energy is the ability of an object in motion to do work or enact change. It can take on many forms. For instance, water flowing down a waterfall has kinetic energy. In biological systems, particles of light travel and are absorbed by plants to create chemical energy. Animals consume the chemical energy and give off molecules that carry their scent through the air. They also generate kinetic energy when they run away from predators. Entire systems also possess kinetic energy, like the...
43.4K
Enzyme Kinetics01:19

Enzyme Kinetics

104.0K
Enzymes speed up reactions by lowering the activation energy of the reactants. The speed at which the enzyme turns reactants into products is called the rate of reaction. Several factors impact the rate of reaction, including the number of available reactants. Enzyme kinetics is the study of how an enzyme changes the rate of a reaction.
Scientists typically study enzyme kinetics with a fixed amount of enzyme in the controlled environment of a test tube. When more reactant, or substrate, is...
104.0K
Kinetic Molecular Theory: Molecular Velocities, Temperature, and Kinetic Energy03:07

Kinetic Molecular Theory: Molecular Velocities, Temperature, and Kinetic Energy

29.8K
The kinetic molecular theory qualitatively explains the behaviors described by the various gas laws. The postulates of this theory may be applied in a more quantitative fashion to derive these individual laws.
29.8K
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

246
Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
246

You might also read

Related Articles

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

Sort by
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

Leveraging mathematical models to predict and control T-cell activation.

PLoS computational biology·2026
Same author

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

iScience·2026
Same author

From FAIR to CURE: guidelines for computational models of biological systems.

NPJ systems biology and applications·2026
Same journal

conMItion: an R package adjusting confounding factors for associations in multi-omics.

Bioinformatics (Oxford, England)·2026
Same journal

SpaMFG: a Spatial Multi-omics Integration Method based on Feature Grouping.

Bioinformatics (Oxford, England)·2026
Same journal

CSCN: Inference of Cell-Specific Causal Networks Using Single-Cell RNA-Seq Data.

Bioinformatics (Oxford, England)·2026
Same journal

Sparse CCA-Based Mediation Analysis with High-Dimensional Exposures and Mediators.

Bioinformatics (Oxford, England)·2026
Same journal

Enhancing Cross-Context Generalization in Drug Perturbation Prediction with a Multimodal Conditional Diffusion Framework.

Bioinformatics (Oxford, England)·2026
Same journal

Primer Design through Submodular Function Estimation.

Bioinformatics (Oxford, England)·2026
See all related articles

Related Experiment Video

Updated: Jan 28, 2026

Author Spotlight: Optimization of Performance Parameters of the TAGGG Telomere Length Assay
08:23

Author Spotlight: Optimization of Performance Parameters of the TAGGG Telomere Length Assay

Published on: April 21, 2023

3.6K

Benchmarking optimization methods for parameter estimation in large kinetic models.

Alejandro F Villaverde1, Fabian Fröhlich2,3, Daniel Weindl2

  • 1Bioprocess Engineering Group, IIM-CSIC, Vigo, Spain.

Bioinformatics (Oxford, England)
|March 1, 2019
PubMed
Summary
This summary is machine-generated.

Estimating kinetic model parameters is challenging. A hybrid metaheuristic combining global scatter search with local interior point methods, using adjoint-based sensitivities, offers superior performance over multi-start local searches for complex optimization problems.

More Related Videos

Electrospinning Fundamentals: Optimizing Solution and Apparatus Parameters
07:57

Electrospinning Fundamentals: Optimizing Solution and Apparatus Parameters

Published on: January 21, 2011

65.8K
CMAP Scan MUNE MScan - A Novel Motor Unit Number Estimation MUNE Method
08:25

CMAP Scan MUNE MScan - A Novel Motor Unit Number Estimation MUNE Method

Published on: June 7, 2018

12.9K

Related Experiment Videos

Last Updated: Jan 28, 2026

Author Spotlight: Optimization of Performance Parameters of the TAGGG Telomere Length Assay
08:23

Author Spotlight: Optimization of Performance Parameters of the TAGGG Telomere Length Assay

Published on: April 21, 2023

3.6K
Electrospinning Fundamentals: Optimizing Solution and Apparatus Parameters
07:57

Electrospinning Fundamentals: Optimizing Solution and Apparatus Parameters

Published on: January 21, 2011

65.8K
CMAP Scan MUNE MScan - A Novel Motor Unit Number Estimation MUNE Method
08:25

CMAP Scan MUNE MScan - A Novel Motor Unit Number Estimation MUNE Method

Published on: June 7, 2018

12.9K

Area of Science:

  • Computational chemistry
  • Chemical kinetics
  • Optimization algorithms

Background:

  • Kinetic model parameter estimation is crucial but computationally challenging.
  • Local optima and ill-conditioning hinder accurate parameter estimation.
  • A lack of systematic comparison exists for optimization methods on large-scale problems.

Purpose of the Study:

  • To systematically compare different optimization methods for kinetic model parameter estimation.
  • To identify the most effective strategy for handling complex optimization challenges.
  • To provide a robust and accessible implementation for the scientific community.

Main Methods:

  • Evaluation of multi-start deterministic local searches.
  • Assessment of stochastic global optimization metaheuristics.
  • Comparison of hybrid methods combining global and local searches, utilizing parametric sensitivities.

Main Results:

  • Multi-start gradient-based local methods show success due to advances in parametric sensitivity calculations.
  • Hybrid metaheuristics offer improved performance.
  • The best performing method integrates scatter search with interior point methods using adjoint-based sensitivities.

Conclusions:

  • Hybrid metaheuristics, particularly scatter search with interior point methods and adjoint-based sensitivities, are highly effective for kinetic model parameter estimation.
  • The developed implementation facilitates wider adoption of advanced optimization techniques.
  • This study provides a benchmark for selecting appropriate optimization strategies in computational modeling.