[gipp]

The notion that computational reducibility is the key principle underpinning difficulty in life (and probably social) sciences is extremely insightful, and had me optimistic for the second half.

But the author's suggestion to address this problem is just... to chase the combinatorial explosion harder? That's a pretty underwhelming solution. And impossible cost scaling aside, another key part of the problem is that we don't even know how to enumerate what the relevant parameters are. What about the effects of a mouse's environment on natural immune response and drug efficacy, for example? Such a highly roboticized environment would be highly unpleasant for a mouse, presumably, and adverse effects seem well within the realm of possibility.

[eli_gottlieb]

I would think that we have to consider the entire parameter space or model space of a reductionist view of biology as a space of models, then search for the smaller subspace of models with fewer, stiffer parameters. http://www.lassp.cornell.edu/sethna/Sloppy/WhatAreSloppyMode...