Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

You might also read

Related Articles

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

Sort by

Same author

The evolving biology of T cell memory: A dynamic continuum of function and persistence.

Science immunology·2026

Same author

Evaluation of serum antibodies as correlates of protection against norovirus infection and disease.

The Journal of infectious diseases·2026

Same author

Prognostic value of plasma cortisol concentration in dogs with congestive heart failure.

Journal of veterinary internal medicine·2026

Same author

Preventing Disease Emergence Following Eradication: Application to Mpox.

bioRxiv : the preprint server for biology·2026

Same author

B cell imprinting in children impairs antibodies to the haemagglutinin stalk.

Nature·2026

Same author

IFN-gene signatures in B cells following influenza A and B virus infection and influenza vaccination.

EMBO molecular medicine·2026

Same journal

A guide to CAR T cell therapies: development, current status and future prospects.

Nature reviews. Immunology·2026

Same journal

Macrophages in embryonic development.

Nature reviews. Immunology·2026

Same journal

Glycolytic capacity instructs tumour vasculature and response to immunotherapy.

Nature reviews. Immunology·2026

Same journal

Vaginal NK cells limit epithelial barrier disruption during infection.

Nature reviews. Immunology·2026

Same journal

New insights into progenitor exhausted T cell populations.

Nature reviews. Immunology·2026

Same journal

T cell engagers in autoimmune diseases.

Nature reviews. Immunology·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Jan 2, 2026

Predictive Immune Modeling of Solid Tumors

Predictive Immune Modeling of Solid Tumors

Published on: February 25, 2020

Simulation modelling for immunologists.

Andreas Handel¹, Nicole L La Gruta², Paul G Thomas³

¹Department of Epidemiology and Biostatistics, Health Informatics Institute and Center for the Ecology of Infectious Diseases, University of Georgia, Athens, GA, USA. ahandel@uga.edu.

Nature Reviews. Immunology

|December 6, 2019

Summary

This summary is machine-generated.

Mechanistic simulation models offer a powerful approach to understanding the complex immune system. This review introduces these computational tools and their application in immunological research, particularly for immune responses to infection.

More Related Videos

Microfluidic Co-Culture Models for Dissecting the Immune Response in in vitro Tumor Microenvironments

Microfluidic Co-Culture Models for Dissecting the Immune Response in in vitro Tumor Microenvironments

Published on: April 30, 2021

Xenograft Skin Model to Manipulate Human Immune Responses In Vivo

Xenograft Skin Model to Manipulate Human Immune Responses In Vivo

Published on: June 29, 2022

Related Experiment Videos

Last Updated: Jan 2, 2026

Predictive Immune Modeling of Solid Tumors

Predictive Immune Modeling of Solid Tumors

Published on: February 25, 2020

Microfluidic Co-Culture Models for Dissecting the Immune Response in in vitro Tumor Microenvironments

Microfluidic Co-Culture Models for Dissecting the Immune Response in in vitro Tumor Microenvironments

Published on: April 30, 2021

Xenograft Skin Model to Manipulate Human Immune Responses In Vivo

Xenograft Skin Model to Manipulate Human Immune Responses In Vivo

Published on: June 29, 2022

Area of Science:

Immunology
Computational Biology
Mathematical Modeling

Background:

The immune system's complexity necessitates advanced analytical tools.
Understanding immune component interactions is crucial for predicting outcomes.
Mathematical and computational modeling offer integrated approaches to study immunology.

Purpose of the Study:

To provide an introductory overview of mechanistic simulation models in immunology.
To define and contrast mechanistic models with other immunological modeling approaches.
To review the diverse applications of these models in addressing immunological questions.

Main Methods:

Review of existing literature on mechanistic simulation models.
Definition and conceptual explanation of mechanistic modeling.
Illustrative examples focusing on immune responses to infection.

Main Results:

Mechanistic simulation models provide a framework for probing immunological components.
These models can be used to answer complex questions across various immunological domains.
Examples demonstrate the utility of models in understanding infection-related immune responses.

Conclusions:

Mechanistic simulation models are valuable tools for dissecting immune system complexity.
The principles discussed are broadly applicable to diverse areas within immunology.
Computational modeling enhances our ability to investigate and understand immunological processes.