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Mathematics for understanding disease.

R R Bies1, M R Gastonguay, S L Schwartz

  • 1Department of Pharmaceutical Sciences, University of Pittsburgh, Pittsburgh, Pennsylvania, USA. rrb47@pitt.edu

Clinical Pharmacology and Therapeutics
|April 5, 2008
PubMed
Summary
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Mathematical models in biology range from pure prediction to deep understanding of processes. Current research emphasizes prediction, but the goal is to advance towards comprehensive systems biology models for better biological insight.

Area of Science:

  • Systems Biology
  • Mathematical Modeling in Biology
  • Computational Biology

Background:

  • Mathematical models are applied to biological systems across a spectrum of purposes, from simple prediction to in-depth understanding.
  • Current models often prioritize prediction (e.g., clinical trial simulations, disease progression modeling) over a complete understanding of biological processes.
  • No existing models exist at the extreme ends of this spectrum, indicating a gap between current capabilities and ideal applications.

Purpose of the Study:

  • To advocate for a shift in the application of mathematical models in biology, moving towards a deeper understanding of biological systems.
  • To encourage the development of models that integrate a comprehensive understanding of biological organization, which would inherently improve predictive capabilities.
  • To highlight the importance of systems biology approaches in achieving a more complete comprehension and prediction of disease processes.

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Main Methods:

  • Conceptual framework outlining a continuum of purpose for mathematical models in biology.
  • Discussion on the current emphasis on predictive modeling versus understanding-driven modeling.
  • Argument for transitioning from static, empirical modeling to dynamic, systems biology-focused modeling.

Main Results:

  • The continuum of model purpose ranges from prediction of biological parameters to precise understanding of biological processes.
  • Current modeling efforts are predominantly focused on prediction, with limited emphasis on mechanistic understanding.
  • A universal understanding of biological organization is the ultimate goal, which would encompass precise prediction as a subset.

Conclusions:

  • There is a need to move mathematical modeling in biology towards a greater emphasis on understanding complex biological systems.
  • Systems biology offers a framework for developing models that capture the inherent organization of biological systems.
  • Advancing towards understanding-based models is crucial for improving both comprehension and prediction of disease processes.