People are being dismissive of your comments because to say that proteins are niche in the context of pharma is like saying advertising is niche in the context of Meta and Google.
its all about how you define word "niche", for google, main revenue stream is supported by several pillars: search tech, infra tech, ads tech, ecosystem+network effect, human management. You remove one pillar, and everything is destroyed, so one can say ads is one of the niches in their food chain. I suspect with proteins it is about the same.
> in the context of pharma
there is no context of pharma. Post is about more broad bio-medical publications.
Literally the first line in the comment that started this thread.
that's one of the themes (and you are already working hard to stretch drugs pharma to "biochemistry"), if you can't see other themes in his examples and screenshots, I think this discussion is not interesting to me.
I'm now not entirely sure what your experience is with bio sciences. You're definitely coming at it from an odd angle though!
You never know, maybe you'll end up contributing to our understanding of life, maybe (indirectly) even save a few lives!
life science is one of potential applications if there is an interest and money.
But if you mean in general if you're capable of looking at metabolic pathways where each protein catalyses a step in the pathway, that's definitely interesting. If a certain person has a flawed gene coding for protein X, that could indeed cause a problem.
To find valid answers, you might need to eg. track nodes and states in a graph, to figure all the consequences of a break. Not all types of storage systems/engines are equally good at that.
[1] https://en.wikipedia.org/wiki/Transcription_(biology)
[2] https://en.wikipedia.org/wiki/Translation_(biology)
edit: s/protein pathway/metabolic pathway/
Yes, I built system which traverses paths in graphs with 1B nodes and 10B links in 1h on affordable server. But that's only one part of the puzzle.