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

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

397
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...
397
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

1.4K
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...
1.4K
Operon Model01:23

Operon Model

2.1K
The operon model represents a fundamental mechanism of gene regulation in prokaryotes, enabling coordinated expression of genes involved in related metabolic or functional pathways. Operons consist of structural genes, a promoter, and an operator, with transcription regulated by repressors, activators, and small effector molecules.Structure and Function of OperonsAn operon is a cluster of structural genes transcribed together under the control of a single promoter. The promoter region...
2.1K
Determination of Multiple Dosing Parameters: Steady-State, Minimum and Maximum Concentrations01:15

Determination of Multiple Dosing Parameters: Steady-State, Minimum and Maximum Concentrations

324
Gentamicin, an aminoglycoside antibiotic, is commonly administered via intermittent intravenous infusion to treat severe infections. An intermittent one-hour infusion of gentamicin, administered at eight-hour intervals, allows for precise control of plasma drug concentrations, minimizing toxicity while ensuring therapeutic efficacy. Pharmacokinetic principles govern the dynamics of plasma concentrations and can be mathematically described using specific equations.The plasma drug concentration...
324
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

310
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...
310
Regulation of Metabolism01:19

Regulation of Metabolism

12.3K
Cellular needs and conditions vary from cell to cell and change within individual cells over time. For example, the required enzymes and energetic demands of stomach cells are different from those of fat storage cells, skin cells, blood cells, and nerve cells. Furthermore, a digestive cell works much harder to process and break down nutrients during the time that closely follows a meal compared with many hours after a meal. As these cellular demands and conditions vary, so do the amounts and...
12.3K

You might also read

Related Articles

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

Sort by
Same author

Resistin, an adipocytokine, offers protection against acute myocardial infarction.

Journal of molecular and cellular cardiology·2007
Same author

Liquid chromatographic analysis of phosphoamino acids at femtomole level using chemical derivatization with N-hydroxysuccinimidyl fluorescein-O-acetate.

Analytica chimica acta·2007
Same author

6-oxy-(acetyl piperazine) fluorescein as a new fluorescent labeling reagent for free fatty acids in serum using high-performance liquid chromatography.

Journal of chromatography. A·2007
Same author

Synthesis and fluorescence properties of 5,7-diphenylquinoline and 2,5,7-triphenylquinoline derived from m-terphenylamine.

Molecules (Basel, Switzerland)·2007
Same author

[Metabolic engineering of terpenoids in plants].

Sheng wu gong cheng xue bao = Chinese journal of biotechnology·2007
Same author

Hedgehog signaling in the murine melanoma microenvironment.

Angiogenesis·2007

Related Experiment Video

Updated: Mar 28, 2026

High-Throughput Metabolic Profiling for Model Refinements of Microalgae
11:07

High-Throughput Metabolic Profiling for Model Refinements of Microalgae

Published on: December 4, 2021

4.4K

Kriging-Based Parameter Estimation Algorithm for Metabolic Networks Combined with Single-Dimensional Optimization and

Hong Wang, Xicheng Wang, Zheng Li

    IEEE/ACM Transactions on Computational Biology and Bioinformatics
    |December 15, 2015
    PubMed
    Summary

    This study presents a novel Kriging-based algorithm for estimating parameters in metabolic network models. The method efficiently optimizes complex biological systems, improving accuracy and speed for molecular mechanism insights.

    More Related Videos

    Author Spotlight: An Optimized Automated Method for Investigating Retinoic Acid Receptors in Neuronal Mitochondria
    08:33

    Author Spotlight: An Optimized Automated Method for Investigating Retinoic Acid Receptors in Neuronal Mitochondria

    Published on: July 28, 2023

    1.1K
    Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
    10:44

    Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

    Published on: December 7, 2021

    2.7K

    Related Experiment Videos

    Last Updated: Mar 28, 2026

    High-Throughput Metabolic Profiling for Model Refinements of Microalgae
    11:07

    High-Throughput Metabolic Profiling for Model Refinements of Microalgae

    Published on: December 4, 2021

    4.4K
    Author Spotlight: An Optimized Automated Method for Investigating Retinoic Acid Receptors in Neuronal Mitochondria
    08:33

    Author Spotlight: An Optimized Automated Method for Investigating Retinoic Acid Receptors in Neuronal Mitochondria

    Published on: July 28, 2023

    1.1K
    Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
    10:44

    Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

    Published on: December 7, 2021

    2.7K

    Area of Science:

    • Systems Biology
    • Metabolic Engineering
    • Computational Biology

    Background:

    • Metabolic network models offer deep insights into organismal molecular mechanisms.
    • Parameter estimation in these models is crucial but challenging due to nonlinearity and large parameter spaces.
    • Traditional optimization algorithms struggle with the complexity of metabolic network models.

    Purpose of the Study:

    • To develop an efficient optimization approach for metabolic network parameter estimation.
    • To address the limitations of traditional algorithms in handling high nonlinearity and large parameter variations.
    • To construct accurate metabolic network models through precise parameter estimation.

    Main Methods:

    • A Kriging-based algorithm incorporating an expected improvement and mutual information (EI&MI) infill sampling criterion.
    • Domain decomposition strategy using principal component analysis to reduce computation time.
    • Combination of single-dimensional optimization and dynamic coordinate perturbation for accelerated convergence.

    Main Results:

    • The proposed algorithm effectively estimates parameters for metabolic networks.
    • Demonstrated high accuracy in parameter values for the arachidonic acid metabolic network.
    • Achieved precise parameter estimation within a limited number of iterations.

    Conclusions:

    • The novel Kriging-based algorithm provides an effective solution for metabolic network parameter estimation.
    • The EI&MI criterion and domain decomposition strategy enhance modeling accuracy and computational efficiency.
    • This approach facilitates a deeper understanding of molecular mechanisms in biological systems.