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

Synthetic Biology02:55

Synthetic Biology

5.8K
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...
5.8K
Growth Models with Integration: Problem Solving01:27

Growth Models with Integration: Problem Solving

155
In population modeling, integration provides a systematic way to determine accumulated quantities from known rates of change. One such application arises in ecology, where the total weight of a fish population in a body of water is referred to as its biomass. When the rate of growth of this biomass is known as a function of time, calculus can be used to determine the total biomass at a future date.Growth Rate and Biomass FunctionLet the growth rate of the fish population be represented by a...
155
Modeling with Differential Equations01:25

Modeling with Differential Equations

281
Population dynamics can be described mathematically by considering the population size P(t) as a function of time. The rate of change of the population is then represented by the derivative of P(t). A simple assumption is that the rate of growth is proportional to the size of the population itself. This leads to an exponential growth model, where the population increases rapidly without bound. While this is a useful first approximation, it does not reflect realistic long-term...
281
Mathematical Modeling: Problem Solving01:29

Mathematical Modeling: Problem Solving

535
Mathematical modeling transforms real-world scenarios into mathematical expressions, allowing for structured problem-solving and analysis. This process involves defining the situation, assigning variables to measurable quantities, selecting an appropriate model, and solving the resulting equation. Such models are invaluable in finance, providing precise methods to evaluate investments, loans, and repayment structures.A widely used example is the calculation of fixed monthly payments on a loan,...
535
Molecular Models02:00

Molecular Models

45.8K
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.
45.8K
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

342
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...
342

You might also read

Related Articles

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

Sort by
Same author

TabularQual: A spreadsheet-based format for annotating and curating logical models in SBML-qual.

bioRxiv : the preprint server for biology·2026
Same author

MarkerScout: A Disease-Agnostic Machine Learning Framework for Biomarker Prediction from Multi-Scale Mechanistic Models.

bioRxiv : the preprint server for biology·2026
Same author

A comprehensive mechanistic multicellular model of the human immune system spanning 11 diseases.

Frontiers in immunology·2026
Same author

MechAInistic: An LLM-guided Multi-Agent System for Reasoning over Genome-Scale Constraint-Based Metabolic Models.

bioRxiv : the preprint server for biology·2026
Same author

AutoRNAseq: Automated Bulk RNA-seq Analysis Pipeline.

bioRxiv : the preprint server for biology·2026
Same author

Spermidine biosynthesis by hypervirulent <i>Francisella tularensis</i> promotes fitness and salvages adenine.

Journal of bacteriology·2026

Related Experiment Video

Updated: Apr 16, 2026

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

12.0K

Integrating interactive computational modeling in biology curricula.

Tomáš Helikar1, Christine E Cutucache2, Lauren M Dahlquist2

  • 1Department of Biochemistry, University of Nebraska-Lincoln, Lincoln, Nebraska, United States of America.

Plos Computational Biology
|March 20, 2015
PubMed
Summary

Computational modeling tools like Cell Collective enhance biology education by engaging students in interactive simulations, moving beyond traditional memorization for deeper understanding.

More Related Videos

Using Mouse Mammary Tumor Cells to Teach Core Biology Concepts: A Simple Lab Module
10:39

Using Mouse Mammary Tumor Cells to Teach Core Biology Concepts: A Simple Lab Module

Published on: June 18, 2015

13.9K
Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches
10:50

Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches

Published on: June 21, 2022

2.3K

Related Experiment Videos

Last Updated: Apr 16, 2026

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

12.0K
Using Mouse Mammary Tumor Cells to Teach Core Biology Concepts: A Simple Lab Module
10:39

Using Mouse Mammary Tumor Cells to Teach Core Biology Concepts: A Simple Lab Module

Published on: June 18, 2015

13.9K
Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches
10:50

Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches

Published on: June 21, 2022

2.3K

Area of Science:

  • Life Sciences Education
  • Computational Biology
  • Pedagogical Innovation

Background:

  • Traditional life sciences education relies heavily on textbooks and memorization.
  • Engineering fields commonly use computational tools for complex process simulation.
  • A gap exists in integrating advanced computational methods into biology curricula.

Purpose of the Study:

  • To explore the feasibility of the Cell Collective platform as a pedagogical tool in university-level biology courses.
  • To foster student engagement, creativity, and higher-level thinking through interactive biological modeling.
  • To provide a non-intimidating pathway for incorporating mathematical and computational concepts into biology education.

Main Methods:

  • Implementation of the Cell Collective Web-based platform in undergraduate and graduate biology courses.
  • Development of a new 'In Silico Biology' course focused on building and simulating biological models.
  • Integration of modeling and simulation modules into existing traditional biology courses (e.g., T cell differentiation, cell cycle regulation).

Main Results:

  • The Cell Collective platform demonstrated feasibility for university-level biology education.
  • Students showed increased engagement and a hands-on approach to learning complex biological processes.
  • The technology facilitated the integration of computational and mathematical concepts for students with limited mathematical backgrounds.

Conclusions:

  • Computational modeling tools, such as Cell Collective, offer a promising new teaching method for biology.
  • Interactive simulations can significantly enhance student understanding and higher-level thinking in biological sciences.
  • This approach supports the 'Vision and Change' initiative for modernizing undergraduate biology education.