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: Overview of Compartment Models01:21

Mechanistic Models: Overview of Compartment Models

174
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...
174
Molecular Models02:00

Molecular Models

40.9K
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.
40.9K
Synthetic Biology02:55

Synthetic Biology

5.0K
Synthetic biology is an interdisciplinary science that involves using principles from disciplines such as engineering, molecular biology, cell biology, and systems biology. It involves remodeling existing organisms from nature or constructing completely new synthetic organisms for applications such as protein or enzyme production, bioremediation, value-added macromolecule production, and the addition of desirable traits to crops, to name a few.
Golden rice
Golden rice is a genetically modified...
5.0K
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

107
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...
107
Energy Diagrams, Transition States, and Intermediates02:13

Energy Diagrams, Transition States, and Intermediates

17.5K
Free-energy diagrams, or reaction coordinate diagrams, are graphs showing the energy changes that occur during a chemical reaction. The reaction coordinate represented on the horizontal axis shows how far the reaction has progressed structurally. Positions along the x-axis close to the reactants have structures resembling the reactants, while positions close to the products resemble the products.  Peaks on the energy diagram represent stable structures with measurable lifetimes, while...
17.5K
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

89
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...
89

You might also read

Related Articles

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

Sort by
Same author

Type 2 diabetes disrupts T-tubule and RyR2 organization in male but not in female rat ventricular muscle.

American journal of physiology. Heart and circulatory physiology·2026
Same author

Verification and reproducible curation of the BioModels repository.

PLoS computational biology·2025
Same author

A mathematical model of metacarpal subchondral bone adaptation, microdamage and repair in racehorses.

Journal of the Royal Society, Interface·2025
Same author

Danicamtiv increases cardiac mechanical efficiency.

The Journal of physiology·2025
Same author

Left ventricular myocardial molecular profile of human diabetic ischaemic cardiomyopathy.

EMBO molecular medicine·2025
Same author

Thermodynamically consistent, reduced models of gene regulatory networks.

Royal Society open science·2025

Related Experiment Video

Updated: Sep 21, 2025

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
10:58

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

Published on: July 25, 2013

17.2K

A semantics, energy-based approach to automate biomodel composition.

Niloofar Shahidi1, Michael Pan2,3,4, Kenneth Tran1

  • 1Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand.

Plos One
|June 3, 2022
PubMed
Summary

We developed a new method for automatically composing biosimulation models using bond graphs and semantic annotations. This approach simplifies the integration of complex biological models, enhancing systems biology research.

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

3.9K
Modeling an Enzyme Active Site using Molecular Visualization Freeware
14:37

Modeling an Enzyme Active Site using Molecular Visualization Freeware

Published on: December 25, 2021

10.2K

Related Experiment Videos

Last Updated: Sep 21, 2025

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
10:58

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

Published on: July 25, 2013

17.2K
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

3.9K
Modeling an Enzyme Active Site using Molecular Visualization Freeware
14:37

Modeling an Enzyme Active Site using Molecular Visualization Freeware

Published on: December 25, 2021

10.2K

Area of Science:

  • Systems Biology
  • Computational Biology
  • Biophysics

Background:

  • Hierarchical modeling is crucial for complex biological systems but faces challenges in model composition and integration.
  • Existing modeling schemes often lack support for seamless hierarchical composition.
  • Integrating diverse biosimulation models requires deep knowledge of individual components and assumptions.

Purpose of the Study:

  • To propose an automated and reliable approach for composing biosimulation models.
  • To address the challenges in integrating complex, large-scale biological models.
  • To facilitate the creation of more comprehensive biological systems models.

Main Methods:

  • Utilized bond graphs to integrate physical, thermodynamic, and biological semantic aspects of modeling.
  • Employed semantic annotations to automate the recognition of common model components.
  • Developed a methodology for the confident and automatic composition of biosimulation models.

Main Results:

  • Successfully coupled a Ras-MAPK cascade model with an upstream EGFR activation model.
  • Demonstrated the effectiveness of the proposed approach in model integration.
  • Validated the use of bond graphs and semantic annotations for automated model composition.

Conclusions:

  • The proposed approach enables automatic and confident composition of biosimulation models.
  • Semantic annotations significantly improve the recognition of common components for integration.
  • This methodology aids researchers in accessing and building more comprehensive biological systems models.