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Author Spotlight: Advanced Enteroid Model for Studying Host-Pathogen Interactions
Published on: April 5, 2024
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Trends in mathematical modeling of host-pathogen interactions.
Jan Ewald1, Patricia Sieber1, Ravindra Garde1,2
1Matthias Schleiden Institute, Bioinformatics, Friedrich Schiller University Jena, Ernst-Abbe-Platz 2, 07743, Jena, Germany.
Cellular and Molecular Life Sciences : CMLS
|November 29, 2019
Summary
Mathematical modeling aids understanding of host-pathogen interactions. This review highlights dynamic optimization, game theory, and spatial modeling to combat infectious diseases in humans, livestock, and crops.
Area of Science:
- Systems Biology
- Computational Biology
- Mathematical Biology
Background:
- Pathogenic microorganisms pose significant threats to human, animal, and plant health.
- Understanding pathogen infection strategies is crucial for developing effective treatments and preventative vaccinations.
- Host-pathogen interactions are complex, occurring across diverse temporal, spatial, and abstraction scales.
Purpose of the Study:
- To review current mathematical and computational modeling approaches for understanding host-pathogen interactions.
- To emphasize dynamic optimization, game theory, and spatial modeling in systems biology.
- To discuss phenomena like molecular mimicry, crypsis, and defense/counter-defense interplay.
Main Methods:
- Review of mathematical modeling techniques, including dynamic optimization, game theory, and spatial modeling.
- Integration of computational approaches to analyze host-pathogen dynamics.
- Discussion of combined modeling strategies for complex interactions.
Main Results:
- Mathematical modeling offers diverse approaches to study host-pathogen interactions.
- Dynamic optimization, game theory, and spatial modeling are key trends in systems biology.
- Combined modeling approaches effectively illuminate intricate host-pathogen relationships.
Conclusions:
- Mathematical modeling provides valuable insights into host-pathogen dynamics.
- A variety of computational and mathematical methods are available for analyzing these interactions.
- Guidance is offered to non-experts for selecting appropriate modeling approaches and fostering interdisciplinary understanding.
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