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Quantitative Bioscience for the 21st Century

Quantitative Bioscience for the 21st Century AbstractUsing a carefully chosen set of examples, we illustrate the importance and ubiquity of quantitative reasoning in the biological sciences. The examples range across many different levels of biological organization, from diseases through ecosystems, and the problems addressed range from basic to applied. In addition to the overall theme that mathematical and statistical approaches are essential for understanding biological systems, three particular and interacting mathematical themes emerge. First, nonlinearity is pervasive; second, inclusion of stochasticity is essential; and third, issues of scale are common to all applications of quantitative approaches. Future progress in understanding many biological systems will depend on continued applications and developments in these three areas, and on understanding how nonlinearity, stochasticity, and scale interact. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png BioScience Oxford University Press

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References (48)

Publisher
Oxford University Press
Copyright
© 2005 American Institute of Biological Sciences
Subject
Overview Articles
ISSN
0006-3568
eISSN
1525-3244
DOI
10.1641/0006-3568(2005)055[0511:QBFTSC]2.0.CO;2
Publisher site
See Article on Publisher Site

Abstract

AbstractUsing a carefully chosen set of examples, we illustrate the importance and ubiquity of quantitative reasoning in the biological sciences. The examples range across many different levels of biological organization, from diseases through ecosystems, and the problems addressed range from basic to applied. In addition to the overall theme that mathematical and statistical approaches are essential for understanding biological systems, three particular and interacting mathematical themes emerge. First, nonlinearity is pervasive; second, inclusion of stochasticity is essential; and third, issues of scale are common to all applications of quantitative approaches. Future progress in understanding many biological systems will depend on continued applications and developments in these three areas, and on understanding how nonlinearity, stochasticity, and scale interact.

Journal

BioScienceOxford University Press

Published: Jun 1, 2005

Keywords: Keywords mathematics ecosystems evolution mathematical biology nonlinearity

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