Parallels between Biology and Computing

Computing is driven inexorably toward multi cell architectures to manage ever-growing complexity


As computing becomes an ever more pervasive part of our modern lives, we naturally look to understand it in terms of what we know of other complex phenomena such as biology. And vice versa. On the one hand, biological systems show computing professionals the way to the exceedingly sophisticated kinds of collaboration found in biological organisms: collaborations between cells, between tissues, between organs and even between organisms collaborating/competing in an ecology. On the other hand, computing systems are recent and are human designed. We can still remember the stages of evolution in computing and thereby perhaps get insight into the evolution of computing that may have had parallels in biology in the mists of prehistory.

Parallels between biology and computing systems include:

The most recent, and most obvious parallel is that both rely on multicellularity to enable complexity to grow beyond the limits manageable in a single cell or single computer. Multicellullarity itself evolves from single-cell architectures because of its inherent advantages. The most primitive multicellular systems have few types of specialized cells.  They become more sophisticated and capable by exploiting more cells and more types of cells.  At present we can only compare the simplest biological examples with the most complex computing examples  because multicellular computing is in its infancy.

Examples in Biology

Simple Metazoans (i.e., multicellular organisms) include:

Examples in Computing

Wikipedia, large public database services (e.g., EMBL/EBI Hinxton GenBank), various "clouds" (Google's Cloud, Amazon's EC2), Social networks (Facebook, Twitter), Massively Multiplayer Online Role Playing Games (World of Warcraft, EverQuest, Second Life) and instant messaging, chat and VOIP systems (e.g., Skype). The largest and most familiar, and those about which more data is available, are:

Note that Facebook and EBay, while among the largest multicellular computing systems, are comparable to Placozoa, the smallest Metazoan. And Google, by far the largest multicellular computing system is far simpler than a jellyfish. Moreover, a jellyfish is self organizing, self sustaining, and self reproducing whereas Google is none of those things.

Neither biological nor computing systems advance just by growing more and more "cells" of one type. They seem to prefer to specialize and exploit more types.  The chart below, based on 2009 data, has far too few data points to support a firm conclusion, yet it indicates a functional relationship, shared by both realms, between the number of "cells" and the number of "cell" types.


relationship between number of cells and number of types



Last revised 5/27/2014