Date: June 3rd, 2011
Cate: Systems, Uncategorized
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Thinking in biological systems with help from Ed

My brilliant polymath friend Ed Rietman sent me a fun paper to read the other day.  He used to head up our Nanotechnology and optics research at Starlab. He works on cancer research, phononic crystals and a host of other deeply interesting fields.  He is working on a bench set-up in his basement that will test a low energy desalinization method using acoustic waves as well as an optical analog to the event horizon of a black hole.  Pretty cool stuff, I always learn a lot listening to Ed.

Tree of eukaryota

Learning new mental models of how things works allows one to synthesize models as analogs for other areas.  Combining investing, finance, risk, behavior, science and biological processes into functional tools and ways of thinking can be very powerful. My book project (The Long Game: mental models for better investing and capital allocation) uses biological, ecological, statistical and social processes to explain how to invest and allocate capital.

Ed sent me a cool paper the other day which I read on the train for fun.  It is titled: Cancer tumors as Metazoa 1.0: tapping genes of ancient ancestors. The general idea is that cancer is a process derived from older cellular functions that exist inactive in the genome and only being expressed under environmental stresses.  The cool idea is that legacy genomic functions are carried forward and cause cancer.  The reason this is so interesting as a field of research is that it would mean that cancer has a finite set of expression types instead of unlimited types. One of the interesting points in the paper is that most plants don’t get cancer and how tumors can often express themselves with hundreds of cell types.

The paper is thankfully simply written so a hobbyist like me can follow along. The mental model of an evolved system still retaining legacy functions which may express themselves detrimentally to the organism is quite interesting.  It is a trade off between functional learning, reproductive progress, climbing a complexity fitness hill and embedded risk. Collecting and synthesizing models of how things work is a hobby of mine, with a friend like Ed, you never know what you can learn that lets you think about the world in a whole new way.

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