Biomedical Engineering Reference
In-Depth Information
Figure 2 . Bacterial chemotaxis. Should the bacterium (center) exploit the currently available
patch of food, or explore, in hopes of finding richer patches elsewhere (e.g., at right)? Many
species solve this problem by performing a random walk (jagged line), tumbling randomly
every so often. The frequency of tumbling increases when the concentration of nutrients is
high, making the bacterium take long steps in resource-poor regions, and persist in resource-
rich ones (7-9).
complexity (10), the nature of organization (11), the relationship between physi-
cal processes and information and computation (12), and the origins of complex-
ity in nature and its increase (or decrease) over time. There is dispute whether
such a science is possible, and if so whether it would be profitable. I think it is
both possible and useful, but most of what has been done in this area is very far
from being applicable to biomedical research. Accordingly, I shall pass it over,
with the exception of a brief discussion of some work on measuring complexity
and organization that is especially closely tied to data analysis.
"Topics" go in the left-hand corner. Here are what one might call the "ca-
nonical complex systems," the particular systems, natural, artificial and fictional,
which complex systems science has traditionally and habitually sought to under-
stand. Here we find networks (see Part II, chapter 4, by Wuchty, Ravasz, and
Barabási, this volume), turbulence (13), physicochemical pattern formation and
biological morphogenesis (14,15), genetic algorithms (16,17), evolutionary dy-
namics (18,19), spin glasses (20,21), neuronal networks (see Part III, section 5,
this volume), the immune system (see Part III, section 4, this volume), social
insects, ant-like robotic systems, the evolution of cooperation, evolutionary eco-
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