Sure, but is it meaningful? What predictions does it enable that are sufficiently borne out by reality to make it seem likely that less easily testable predictions on the same basis may likewise prove sound?
I mean, I can as well say that chalk and cheese are alike in that both have mass, occupy space, and leave a streak behind when you rub them on something. It is a true statement, but what does it help me predict about either?
I think the only real takeaways on the coding/biology comparison are applying base-level informatic systems ideas to explain some biological developments, and in reverse looking at biological system mechanics as inspiration for designed systems.
I don't think the 'chemistry is an OPERATING SYSTEM' level of handwaving is sufficient to glean insights, but understanding general systems-level interactome patterns of how proteins interact does help provide knowledge about how natural and designed systems can self-regulate, how they fail, how they can be structured, etc.
Sure, at that level it makes sense. The trouble seems to be that in order to know that that's the level at which it makes sense, you need to know considerably more about informatics than is the default among programmers who like to indulge in this kind of speculation. Kind of a Dunning-Kruger problem, maybe; there certainly was a time when I likewise didn't know what I didn't know.
I mean, I can as well say that chalk and cheese are alike in that both have mass, occupy space, and leave a streak behind when you rub them on something. It is a true statement, but what does it help me predict about either?