Enter the 36 chambers of infrastructure wu-tang

Saturday, June 23, 2007

The developmental biology of infrastructure

Biologically-inspired technologies have been a research topic for years, autonomic computing and epidemic protocols being a couple of examples. These techniques often have very attractive properties to go with their fun names: scaling, self-healing, resilience, blah, blah, blah. I think about infrastructure and have taken some different things from biology.

The unfortunately named Universal Genetic Code (UGC) and the other, extremely similar variants found in mitochondrial DNA and other small organisms, evolved. We're used to DNA being the stuff of evolution (RNA fans save your flame mails), so the code itself evolving is a bit of a brain bender. Think of it as meta-evolution.

The end of evolution for the UGC happened billions of years ago. Experts call this "early fixation.". The code itself is a marvel of efficiency. It resists exactly the sort of errors to which the transcription machinery is prone. When a transcription error gets through, chances are the erroneous amino acid will have properties similar enough to the correct one that there is little functional difference in the geometry of the final protein. We can appreciate just how spectacular it is because we can almost completely quantify its environment, something simply out of the question with complete organisms. Physics, chemistry, geometry.

The high school biology textbook version of how genes evolve goes something like this: mutation and crossover. Mostly crossover. Read chapters 5 through 7 for Monday.

Reality, as expected, is far richer. Enter Systems Biology and Evolutionary Developmental Biology (evodevo). I can't do justice to the topics in a blog post, but the important idea is this: genes change very slowly, while the gene regulation networks that control their expression are incredibly complex and evolve rapidly.

The bottom of the stack is ridiculously efficient, defined almost entirely by physical constraints, and completely static. Up a level we see simple, modular structures that can be assembled in a variety of ways, and that change very slowly. Finally, at the top, we see the incredible complexity and the roiling expression of evolutionary change.

UGC -> genes -> regulation networks
hardware infrastructure -> software infrastructure -> applications

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