|
|
|
|
|
|
by HarHarVeryFunny
17 days ago
|
|
|
I think that as you ascend the scale of complexity, and just system size, then necessarily empiricalism and rote learning/memorization has to take over from more reductionalist explanations. Physics, whether at atomic level, or on a much larger scale, is simple enough that reductionism usually works and you can calculate behavior from first principles using a few memorized "laws" Biology is well past the point of complexity where you can do this most of the time, unless perhaps you are at the level of aspects of cellular behavior that can be analyzed in terms of chemistry. Chemistry is in-between physics and biology in terms of complexity. In simple cases chemistry can be explained in terms of physics, but as AlphaFold has shown when you get to a certain level of complexity (in this case protein folding) empiricism takes over and you need to perform experiments and memorize results. I think modern science and philosophy has a reasonable understanding of what life is, even if you disagree. This is certainly more a matter of philosophy than science, but it seems the best definition of life is based on the ability of a system to actively maintain a boundary between itself and the external world, thereby combating the 2nd "law" (statistical tendency) of thermodynamics. Maybe an interesting/useful definition (which is somewhat arbitrary) also needs to involve something like consuming energy/resources from the environment. |
|
|
Only in the most hand-wavey sense. Actual simulation of the cell interior with even comically coarse grained models is prohibitively expensive. It comes up a lot in neuroscience where it sure would be nice to be able to credibly simulate even a single neuron at the molecular level. (I'm several years out of date on the state of that field so it's possible someone managed to pull it off in the meantime but even if so the broader point still stands.)