Biology by the Numbers
2004
### Contents
#### News
Life's Patterns: No Need to Spell It Out?
[The New Math of Clinical Trials][1]
[Making Sense of a Heart Gone Wild][2]
#### Viewpoints
Introductory Science and Mathematics Education for 21st-Century Biologists
W. Bialek and D. Botstein
[Uses and Abuses of Mathematics in Biology][3]
R. M. May
#### Reviews
Evolutionary Dynamics of Biological Games
M. A. Nowak and K. Sigmund
Inferring Cellular Networks Using Probabilistic Graphical Models
N. Friedman
Related STKE, SAGE KE, and NextWave material at [www.sciencemag.org/sciext/mathbio][4], and Book Review
T he benefits of interdisciplinary collaborations and the need for researchers to read and think broadly have become truisms of today's scientific world. In this special issue of Science , as well as in Science 's online sites, our keen-sighted contributors report on gleanings from their travels through the lands of mathematics and biology.
Bialek and Botstein (p. [788][5]) propose incorporating mathematical and quantitative approaches into biological sciences curricula, not merely as prerequisite courses to be suffered as a rite of passage but as full-fledged components of the training of a contemporary scientist. May (p. 790) illustrates the insightful use and the unfortunate misuse of mathematical models, with reference to the construction of population genetics on the basis of qualitative Darwinian theory and to modern-day epidemiological wildfires. In a primer for analyzing the challenges of adapting to a world that adapts to you, Nowak and Sigmund (p. 793) review the burgeoning dialogue among evolution, ecology, and game theory. Friedman (p. 799) continues the theme of uncertainty by describing the application of probabilistic graphical models to organizing disparate biological data from genomics, proteomics, and other “omic”-scale projects. Rounding out this topic, Ronquist's Book Review (p. [767][6]) assesses current quantitative approaches to inferring phylogenetic trees.
The News section describes three ways in which researchers are applying mathematics, sometimes controversially, to long-standing biological problems. Some are using differential equations to see whether simple dynamical processes can bridge a presumed “information gap” between the amount of information in organisms' genomes and the kaleidoscopic variety of patterns found in the natural world (Cho, p. [782][7]). One statistician proselytizes for a Bayesian approach to clinical trials, which would upend current designs by requiring researchers to take past studies into account (Couzin, p. [784][1]). Finally, Mackenzie (p. 786) describes early efforts to unravel how sudden electrical storms send a normally beating heart reeling into chaotic fibrillation and why defibrillators are so unaccountably good at restoring order.
Mathematics pervades the study of signal transduction mechanisms. At Science 's STKE (stke.sciencemag.org/cgi/content/abstract/stke.2192004eg3v1), explore interactive computational models of cell signaling and discuss them with the authors in Forums. Applications include modeling of mechanosensitive channel function, calculation of calcium transients in tiny subcellular compartments, and computational prediction of key residues in protein interaction surfaces.
In their SAGE KE ( ) Perspective, Rueppell et al . discuss the use of social insects such as bees and ants to investigate the influences of social evolution on aging. They also illustrate how mathematics describes the relation between individual-and colony-level demography.
Throughout February, Science 's Next Wave ( ) will serve as your guide to careers at the math-biology interface. It will profile young scientists and training programs and provide practical advice on starting out and managing a career at the intersection of these disciplines.
[1]: /lookup/doi/10.1126/science.303.5659.784
[2]: /lookup/doi/10.1126/science.303.5659.786
[3]: /lookup/doi/10.1126/science.1093411
[4]: http://www.sciencemag.org/sciext/mathbio
[5]: /lookup/doi/10.1126/science.1095480
[6]: /lookup/doi/10.1126/science.1094283
[7]: /lookup/doi/10.1126/science.303.5659.782
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