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

Multicompartment Models: Overview01:14

Multicompartment Models: Overview

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,...
Pharmacodynamic Models: Link Model and Systems Pharmacodynamic Model01:14

Pharmacodynamic Models: Link Model and Systems Pharmacodynamic Model

The link model is a fundamental pharmacokinetic-pharmacodynamic (PK–PD) approach to account for delayed drug responses when the observed effect does not immediately correlate with the drug's plasma concentration peak. This delay is mathematically addressed by introducing an effect compartment concentration, Ce, which is kinetically linked to the plasma concentration, Cp, via a first-order rate constant, ke0. The linkage allows for a more accurate prediction of drug effects over time. A higher...
Mechanistic Models: Overview of Compartment Models01:21

Mechanistic Models: Overview of Compartment Models

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...
Molecular Models02:00

Molecular Models

Physical models representing molecular architectures of chemical compounds play essential roles in understanding chemistry. The use of molecular models makes it easier to visualize the structures and shapes of atoms and molecules.
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

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...
Model Approaches for Pharmacokinetic Data: Physiological Models01:15

Model Approaches for Pharmacokinetic Data: Physiological Models

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...

You might also read

Related Articles

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

Sort by
Same author

Comparison of airway mucin 5AC and 5B expression in preterm-born adults and asthma.

ERJ open research·2026
Same author

Oxylipin-mediated metabolic signatures of symbiosis homeostasis and thermal stress in a model sea anemone.

The ISME journal·2026
Same author

LIPID MAPS: Powering discovery in lipidomics.

Science signaling·2026
Same author

Long COVID and risk of incident cardiovascular disease: a prospective cohort study using the Multimorbidity Integrated Registry Across Care Levels in Stockholm (MIRACLE-S) cohort.

EClinicalMedicine·2026
Same author

Potent Neuronal Nicotinamide Adenine Dinucleotide-Boosting Tetrahydroquinoxalines: Structure-Activity Relationships and Early Drug Metabolism and Pharmacokinetics Evaluation.

ACS medicinal chemistry letters·2026
Same author

Author Correction: Octadecanoids as emerging lipid mediators in cnidarian-dinoflagellate symbiosis.

Communications biology·2026
Same journal

The ACS at 150: The History of Analytical Chemistry Publications and a Century of Progress.

Analytical chemistry·2026
Same journal

Machine Learning-Enabled Image Analysis of Complex Chemical Mixtures: Synthetic Urine Droplets as a Test System.

Analytical chemistry·2026
Same journal

H<sub>2</sub>O<sub>2</sub>/Viscosity Tandem-Locked Fluorescent Probes Based on an In Situ Fluorophore Synthesis Strategy for Colitis Imaging and Diagnosis.

Analytical chemistry·2026
Same journal

TopoStitcher: A Geometric-Topological Structure-Guided Stitching Framework for Single-Molecule Localization Microscopy.

Analytical chemistry·2026
Same journal

Noninvasive SERS Immunosensing of Tyrosinase for Melanoma Monitoring via Microneedle Sampling Integrated with Satellite-Structured Bifunctional Nanozymes.

Analytical chemistry·2026
Same journal

Label-Free Electrochemical CRISPR Platform Gated by Allosteric Transcription Factors for Ultrasensitive Small-Molecule Detection.

Analytical chemistry·2026
See all related articles

Related Experiment Video

Updated: May 19, 2026

Application of Unsupervised Multi-Omic Factor Analysis to Uncover Patterns of Variation and Molecular Processes Linked to Cardiovascular Disease
08:51

Application of Unsupervised Multi-Omic Factor Analysis to Uncover Patterns of Variation and Molecular Processes Linked to Cardiovascular Disease

Published on: September 20, 2024

Building multivariate systems biology models.

Gemma M Kirwan1, Erik Johansson, Robert Kleemann

  • 1Bioinformatics Centre, Institute for Chemical Research, Kyoto University, Kyoto, Japan. gemma.kirwan@gmail.com

Analytical Chemistry
|August 4, 2012
PubMed
Summary
This summary is machine-generated.

This study introduces a multivariate analysis workflow to integrate and analyze "omics" data, identifying diglycerides as key hepatic metabolites in diet-induced atherogenesis and therapeutic response.

More Related Videos

Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling (SAHM)
12:26

Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling (SAHM)

Published on: October 11, 2016

Constructing and Visualizing Models using Mime-based Machine-learning Framework
06:19

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Published on: July 22, 2025

Related Experiment Videos

Last Updated: May 19, 2026

Application of Unsupervised Multi-Omic Factor Analysis to Uncover Patterns of Variation and Molecular Processes Linked to Cardiovascular Disease
08:51

Application of Unsupervised Multi-Omic Factor Analysis to Uncover Patterns of Variation and Molecular Processes Linked to Cardiovascular Disease

Published on: September 20, 2024

Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling (SAHM)
12:26

Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling (SAHM)

Published on: October 11, 2016

Constructing and Visualizing Models using Mime-based Machine-learning Framework
06:19

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Published on: July 22, 2025

Area of Science:

  • Systems biology
  • Multivariate data analysis
  • Lipidomics

Background:

  • Integrating large-scale "omics" data presents challenges in managing vast data spaces and removing systematic noise.
  • Systems biology requires robust methods for analyzing complex biological systems and identifying meaningful correlations.

Purpose of the Study:

  • To propose and demonstrate a complementary multivariate analysis workflow for integrating disparate "omics" data.
  • To identify specific and unique sample correlations within complex biological datasets.

Main Methods:

  • The workflow combines Principal Component Analysis (PCA), Orthogonal Projections to Latent Structures Discriminant Analysis (OPLS-DA), Orthogonal 2 Projections to Latent Structures (O2PLS), and Shared and Unique Structures (SUS) plots.
  • Applied to lipidomics and free fatty acid data from ApoE3Leiden mice fed an atherogenic diet and treated with fenofibrate, rosuvastatin, or T-0901317.
  • Liquid chromatography-mass spectrometry (LC-MS) was used for metabolite quantification.

Main Results:

  • The workflow successfully integrated "omics" data and identified diglycerides as key hepatic metabolites affected by dietary cholesterol and drug interventions.
  • Diglycerides were highlighted as metabolites of interest in atherogenesis, potentially contributing to chronic liver inflammation.
  • Orthogonal 2 Projections to Latent Structures (O2PLS)-based SUS2 plots indicated that T-0901317 or rosuvastatin treatments normalized diglyceride profiles in high-cholesterol-fed mice.

Conclusions:

  • The proposed multivariate analysis workflow effectively integrates "omics" data and reveals key biological insights.
  • Diglycerides play a significant role in diet-induced atherogenesis and liver inflammation.
  • Specific therapeutic interventions can restore normal diglyceride profiles, offering potential therapeutic strategies.