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26 - Computer Metaphors for the Endothelium

from PART I - CONTEXT

Published online by Cambridge University Press:  04 May 2010

Dexter Pratt
Affiliation:
Genstruct, Cambridge, Massachusetts
William C. Aird
Affiliation:
Harvard University, Massachusetts
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Summary

“It was a dark and stormy night. The Weibel-Palade bodies surged to the surface, releasing their witch's brew into the turbulent surf downstream of the rupture. Neutrophils shuddered to a stop as selectins grappled, tore away, and then finally caught.”

INTRODUCTION

“Endothelial biology is weather.” That is a metaphor, and a bold one, because it compares two systems of enormous complexity and implies that they share fundamental features despite an utterly different scale and mechanism. But is that a “computer” metaphor? Shouldn't this chapter find its metaphors in circuits, signal processing, and the Internet? My answer is “No,” because in the mechanics of computation, the details of technology, we see an entirely artificial landscape, a world dominated by well-defined protocols, regimented structures, and perfect repeatability. It is a world in which “crosstalk,” the secondary interaction between components or processes, is scrupulously avoided. By contrast, crosstalk is the norm in biological systems. Signaling “protocols” exist in biology, but their effect is nuanced and context-dependent, shifting the behavior of systems that are the dynamically balanced product of many competing and overlapping processes.

To find meaningful computer metaphors, we need to look at computer applications that attempt to deal with natural, emergent complexity. The metaphors derived from these applications are not just “computer” metaphors, but are “computable” – they provide insight into the pragmatic construction of systems that can encode biological theories and hypotheses. The scientific process is essentially the discovery and articulation of rules that describe and predict the events we can observe in the world around us. When those rules are expressed in a computable form, algorithms can perform useful inferences about systems and datasets too large for a scientist to reason about.

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Publisher: Cambridge University Press
Print publication year: 2007

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