| Thanks a lot for your kind words! Really like your thoughts! Indeed, lack of time-series observability makes it harder for us to find general patterns or causal events. Definitely agree that biology is the pinnacle of all complexity - IMO something like macroeconomics or human behavior within set systems (society, politics, etc.) is fairly reducible to a very small and finite set of incentives that agents optimise for (food, shelter, status, acceptance, etc.). Given this, Non-linearity and stochasticness still adds up to a general nature of non-determinism for the entire system. With Biology on the other hand is extremely more complicated to study as - correct me if I'm wrong - it's still hard to realise what agents in systems are optimising for. reduction of free energy? reproduction? general homeostasis? etc. and then all these play varying roles in diff contexts, and then we'll still have to figure out how/why self-assembly and "wholes" emerging from smaller "wholes" (... ad infinitum) actually happens. Really fuzzy thoughts but I believe There is some merit in exploring reducibility and observability from a time series perspective while considering effects of synchronity/asynchronity of observability and later how much we can desirably steer systems. Really fuzzy but I hope to work on this a bit more. Thanks a lot for your very interesting comments! Not discouraged at all, love your view on systems theory being a "routine analysis" like statistics, i.e. a very generally applicable layer or meta-science that's an entirely new way to see things, which I should've articulated better in my post. |
I'm mostly thinking individual cells in a multicellular organism (i.e. lung cells in a person). It is indeed very hard to understand what they are optimizing for. Obviously, the organism as a whole is under selective pressure, but I'm not sure how much an individual cell in a given organism actually "feels" the pressure. Like, they undergo many cell cycles during one organism's life, but they're not really evolving or being selected during each cell cycle. Of course, this isn't always true as tumors definitely display selective pressure and evolution. But for normal tissue, I prefer to think of cells as dynamical systems operating under energetic and mass flux constraints. They're also constrained by the architecture of the interactions of the genes and proteins in the cell. All that adds up to something that looks a lot like evolutionarily optimized phenotypes, but I think that might be a bit deceptive, as the underlying process is different. It's not at all clear to me though. You're really getting at some deep questions! You might find this paper interesting in that regard:
https://www.nature.com/articles/nmeth.3254
Regarding reducibility and observability of time series, you might also find work from James (Jim) Sethna's lab at Cornell interesting. The math can be a bit hairy, but I think they do a pretty good job at distilling the concepts down so that they're intuitive. The overall idea is that some complex systems have "sloppiness", like some parts of the system can have any kind of weird, noisy behavior, but they don't change the overall behavior that much. Other parts of the system are "rigid", in that their behavior is tightly connected to the overall behavior.
https://arxiv.org/abs/2111.07176v1
You ought to get yourself connected with some folks at the Santa Fe Institute, if you haven't already. I know one affiliated professor, let me know if you want an introduction. At the very least, if you like podcasts, check theirs out. It's called "Complexity" and it's quite good.