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A modeller's guide for biomedical discovery.
1School of Mathematical Sciences, University of Southampton, Southampton SO17 1BJ, UK.
Disease Models & Mechanisms
|June 23, 2026
Summary
Mathematical modeling drives biological discovery by generating testable hypotheses and falsifying incorrect mechanisms. This approach enhances scientific understanding beyond mere data reproduction and prediction.
Area of Science:
- Biophysics
- Computational Biology
- Systems Biology
Background:
- Classical experimental methods and statistics may not fully address complex biological mechanisms.
- Mathematical and computational models offer powerful tools for scientific inquiry.
Purpose of the Study:
- To explore how mathematical and computational modeling can serve as instruments of discovery in biology.
- To present a model-centered workflow for scientific discovery.
- To discuss the role of universality in model inference.
Main Methods:
- Conceptual framework outlining a model-centered discovery workflow.
- Illustrative example using clonal lineage tracing.
- Analysis of universality in model inference.
Main Results:
- Models translate qualitative biological ideas into quantitative hypotheses.
- Models connect microscopic processes to macroscopic data.
- Models are crucial for falsifying incorrect mechanistic narratives.
Conclusions:
- Intentional use of mathematical modeling accelerates biological discovery.
- A model-centered approach, including understanding universality, is key for advancing biomedical research.
- Practical guidance is provided for integrating modeling into daily research practices.
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