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Biology by numbers: mathematical modelling in developmental biology
Claire J Tomlin1, Jeffrey D Axelrod
1Department of Electrical Engineering and Computer Sciences, University of California Berkeley, Berkeley, California 94720, USA. tomlin@stanford.edu
Nature Reviews. Genetics
|April 19, 2007
Summary
Mathematical modeling is increasingly vital for understanding biological development. This review explores how these models validate hypotheses, generate predictions, and offer new insights into developmental processes.
Area of Science:
- Developmental Biology
- Mathematical Biology
- Systems Biology
Background:
- Mathematical modeling is gaining recognition in developmental biology.
- Models validate experimental data and generate testable predictions.
- They offer novel insights into biological systems and local interactions.
Purpose of the Study:
- To review the potential of mathematical modeling in understanding biological development.
- To examine three specific developmental processes and their corresponding mathematical models.
Main Methods:
- Review of existing literature on mathematical modeling in developmental biology.
- Analysis of three case studies of developmental processes and their models.
Main Results:
- Mathematical models have proven effective in validating hypotheses.
- Model design and testing yield significant experimental predictions.
- Models illuminate the relationship between local interactions and broader biological effects.
Conclusions:
- Mathematical modeling offers a powerful approach to understanding complex developmental processes.
- This interdisciplinary field provides fresh perspectives and drives experimental research.
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