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

Metabolic Rate01:25

Metabolic Rate

1.3K
The human body is a powerhouse of energy, with every cell performing numerous functions that require energy. This energy production and consumption is measured by the metabolic rate, which quantifies the total heat generated by all the body's chemical reactions and mechanical work. This measurement helps to determine the rate of kilocalorie (kcal) consumption needed to fuel all ongoing activities.
The Basal Metabolic Rate (BMR) measures the energy expended at rest.
Several factors influence...
1.3K
Compartment Models: Single-Compartment Model01:14

Compartment Models: Single-Compartment Model

3.3K
The single-compartment model serves as a simplified representation of the human body. This model assumes that the body functions as a single, well-mixed open compartment. When a drug is administered intravenously, it enters the body and quickly distributes uniformly. The drug then undergoes biotransformation and elimination, ultimately leaving the body. The volume of this compartment is referred to as the apparent volume of distribution into which the drug can uniformly distribute. In this...
3.3K
Three-Compartment Open Model01:06

Three-Compartment Open Model

978
The three-compartment open model is a pharmacokinetic model used to describe the distribution and elimination of drugs following extravascular administration. It comprises a central compartment representing the plasma and two peripheral compartments. The highly perfused peripheral compartment represents organs and tissues with a rich blood supply, such as the liver, kidneys, and lungs. The scarcely perfused peripheral compartment represents tissues with lower blood supply, such as adipose...
978
Compartment Models: Two-Compartment Model01:20

Compartment Models: Two-Compartment Model

7.2K
The two-compartment model divides the body into central and peripheral compartments to account for varying blood perfusion rates among organs and tissues, affecting drug distribution. The central compartment includes blood and highly perfused tissues with rapid drug distribution, while the peripheral compartment contains tissues with slower drug distribution. After a single IV bolus dose, the drug concentration is high in plasma and low in tissues. The drug distribution between compartments...
7.2K
Mechanistic Models: Overview of Compartment Models01:21

Mechanistic Models: Overview of Compartment Models

412
Mechanistic models, a category encompassing both physiological and compartmental modeling, differ from empirical models' approaches to incorporating known factors about the systems being modeled. Empirical models describe data with minimal assumptions, while mechanistic models aim to provide a robust description of available data by specifying assumptions and integrating known factors about the system. Compartmental analysis is a key example of a mechanistic model in pharmacokinetics and...
412
Multicompartment Models: Overview01:14

Multicompartment Models: Overview

611
Multicompartment models are mathematical constructs that depict how drugs are distributed and eliminated within the body. They segment the body into several compartments, symbolizing various physiological or anatomical areas connected through drug transfer processes such as absorption, metabolism, distribution, and elimination.
These models offer a more comprehensive representation of drug behavior in the body than one-compartment models. They accommodate the complexity of drug distribution,...
611

You might also read

Related Articles

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

Sort by
Same author

Living bacterial reservoir computers for information processing and sensing.

Cell systems·2026
Same author

Active-learning-guided optimization of cell-free systems for genome-wide transcriptomic profiling reveals progressive layers of regulation.

Nature communications·2026
Same author

Living buildings with living electronics: towards biologically intelligent biohybrids.

Trends in biotechnology·2026
Same author

dAMN: a genome-scale neural-mechanistic hybrid model to predict bacterial growth dynamics.

Bioinformatics (Oxford, England)·2026
Same author

RetroRules 2026: an expanded database combining biochemical and organic reaction templates for pathway discovery.

Nucleic acids research·2025
Same author

Microbial computing: Review and Perspectives.

Biotechnology advances·2025
Same journal

Mapping the 3D Chromosome Organization of a Biosynthetic Gene Cluster by Capture Hi-C (CHi-C).

Methods in molecular biology (Clifton, N.J.)·2026
Same journal

Mapping the 3D Chromosome Organization of Streptomyces by Hi-C.

Methods in molecular biology (Clifton, N.J.)·2026
Same journal

CUT&Tag Epigenomic Profiling of Biosynthetic Gene Clusters in Arabidopsis thaliana.

Methods in molecular biology (Clifton, N.J.)·2026
Same journal

Rhizobium rhizogenes-Mediated Hairy Root Transformation Protocol for Lotus japonicus and Other Legumes.

Methods in molecular biology (Clifton, N.J.)·2026
Same journal

Characterization of Bioactive Saponins from Sea Cucumbers.

Methods in molecular biology (Clifton, N.J.)·2026
Same journal

Methods for Functional Validation of Terpenoid Metabolic Clusters in Nicotiana benthamiana and Aspergillus oryzae.

Methods in molecular biology (Clifton, N.J.)·2026
See all related articles

Related Experiment Video

Updated: Feb 18, 2026

Exploring Mitochondrial Energy Metabolism of Single 3D Microtissue Spheroids Using Extracellular Flux Analysis
08:15

Exploring Mitochondrial Energy Metabolism of Single 3D Microtissue Spheroids Using Extracellular Flux Analysis

Published on: February 3, 2022

3.6K

Extended Metabolic Space Modeling.

Pablo Carbonell1, Baudoin Delépine2,3, Jean-Loup Faulon4,2,3

  • 1Manchester Centre for Fine and Speciality Chemicals (SYNBIOCHEM), Manchester Institute of Biotechnology, University of Manchester, 131 Princess Street, Manchester, M1 7DN, UK. Pablo.carbonell@manchester.ac.uk.

Methods in Molecular Biology (Clifton, N.J.)
|November 25, 2017
PubMed
Summary
This summary is machine-generated.

This study introduces the extended metabolic space, a novel coding system for understanding in vivo chemical processing. It expands the possibilities for synthetic biology applications by defining molecular rules and potential products.

Keywords:
ChassisEnzyme reactionsMetabolic modelingPathwaysProducts

More Related Videos

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

4.3K
Hyperpolarized 13C Metabolic Magnetic Resonance Spectroscopy and Imaging
11:43

Hyperpolarized 13C Metabolic Magnetic Resonance Spectroscopy and Imaging

Published on: December 30, 2016

11.1K

Related Experiment Videos

Last Updated: Feb 18, 2026

Exploring Mitochondrial Energy Metabolism of Single 3D Microtissue Spheroids Using Extracellular Flux Analysis
08:15

Exploring Mitochondrial Energy Metabolism of Single 3D Microtissue Spheroids Using Extracellular Flux Analysis

Published on: February 3, 2022

3.6K
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

4.3K
Hyperpolarized 13C Metabolic Magnetic Resonance Spectroscopy and Imaging
11:43

Hyperpolarized 13C Metabolic Magnetic Resonance Spectroscopy and Imaging

Published on: December 30, 2016

11.1K

Area of Science:

  • Synthetic biology
  • Metabolic engineering
  • Computational biology

Background:

  • Understanding the in vivo chemical processing capacity is vital for advancing synthetic biology.
  • Current methods lack a systematic way to map the full range of molecules processable by biological systems.

Purpose of the Study:

  • To introduce and define the extended metabolic space as a framework for analyzing in vivo chemical processing.
  • To enable the enumeration of all possible substrates and products based on derived metabolic reaction rules.

Main Methods:

  • Development of a coding system based on molecular signatures.
  • Derivation of reaction rules for metabolic reactions.
  • Enumeration of substrates and products based on these rules.

Main Results:

  • The extended metabolic space provides a systematic approach to defining metabolic reaction rules.
  • It allows for the comprehensive enumeration of potential substrates and products within a biological system.
  • This framework expands the scope of molecules that can be engineered in chassis organisms.

Conclusions:

  • The extended metabolic space is a powerful tool for synthetic biology.
  • It enhances control over molecular production, processing, sensing, and release.
  • This approach is crucial for developing sophisticated synthetic biology applications.