This is neat! I’m not fully through it yet, but just wanted to emphasize this:
> And understanding molecular motion is key for everything in biology, everything in biology is vibrating molecules underneath the surface!
Coming into bio as a programmer, this is the absolute sin qua non rule you need to internalize: there are no boundaries between systems, because everything is jiggling atoms. DNA encodes for genes, except the transcription process is heavily mediated by the physical environment and physical constraints of accessing the DNA; RNA transcribes to amino acid strings, except it’s also a molecule, and so sometimes it folds into a structure and just does shit itself; proteins have a function, except sometimes they have many functions, because the “lock and key” metaphor isn’t wrong, except when you’ve got a billion locks and your key’s kinda floppy, it’ll probably fit more than one. Nature plays with physical systems and will repurpose anything to do anything else - the informatics only take you so far, all the real action is vibrating molecules.
> Coming into bio as a programmer, this is the absolute sin qua non rule you need to internalize: there are no boundaries between systems, because everything is jiggling atoms.
(Similar background as you.) Another sine qua non rule is that evolution created biology, it wasn't engineered like software and it doesn't decompose like software. Evolution creates hairballs that has don't respect traditional engineering boundaries and abstraction hierarchies.
From that, along with probabilistic molecular jiggling, we get biological systems that are quite difficult to understand, predict, and control.
It's a good start to realize that what underlies all the understanding of science are simplified predictive models, and usually only statistical models at that.
What this means is that running an experiment in many fields is so difficult that replication is a real challenge. There are so MANY ways you can screw up, or you could just have a statistical fluke that screws you over. Just a tiny contamination or seemingly irrelevant missed step will cause a failure. That's why the idea of having journals composed of failed experiments just doesn't work. Unstated experimental process assumptions are legion. Sometimes an expert can look at the result and see what you've done wrong (like bad contacts in "Electron Band Structure In Germanium, My Ass") and often not even that. Sometimes there's something interesting in the failure, but 99% of the time it's just your pitch is so bad you can't hit the strike zone. Do better!
The things that are easy to replicate (and usually they've been specifically designed that way like Starbucks' over roasted beans), have actually been reduced to engineering. They're not on the edge where scientists can get published. That way perverse incentive madness lies.
Enjoy the controlability of inputs, the repeatability of bugs, the near perfection of compilers and memory allocation, the complete independence of variables while you can. Unless that is, you like Rowhammer and voltage glitch attacks.