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The Human Genome Project was completed almost two decades ago, and somebody solved the protein folding problem recently. Why are we still doing genetics at the

• WJW 6y ago
  I feel this XKCD describes the situation particularly well: https://xkcd.com/1831/ https://xkcd.com/1831/
  • neuronic 6y ago
    Maybe after 4 billion years of evolving our code we will get it right.
• baby 6y ago
  My thought exactly. So this thing is like a VM with a bunch of primitive opcode, why can’t someone write a higher-level language or at least some gadgets
  • WJW 6y ago
    The problem with trying to program genetics is that there is a bunch of code already running on the system and every variable is a global. You can't just start up a new program with minimal impact on the stuff that is already running, like you can in most human-made computers. Also don't forget that the extremely simplified version of the running system looks like this: https://www.sigmaaldrich.com/technical-documents/articles/biology/interactive-metabolic-pathways-map.html https://www.sigmaaldrich.com/technical-documents/articles/bi...
    • flobosg 6y ago
      I wouldn’t call it extremely simplified; you can go simpler: https://science.sciencemag.org/content/351/6280/aad6253 https://science.sciencemag.org/content/351/6280/aad6253
• Yizahi 6y ago
  If I remember correctly "solving" protein folding was essentially some high probability prediction that state A transform to state B with some reasonably high chance, on a big dataset. Or something like that anyway. It's as far from high level work with genetics as creating nanotubes a few molecules long in lab manually is away from industrial production.
• lambdadmitry 6y ago
  The most fundamental reason for that is that it's just not amenable to human mind. We are quite primitive actually, being able to hold only a handful of "things" in our mind at any one time and relying on abstraction to think of more complex things. However, you can't abstract much in biology; there is no locality or separation of concerns, everything affects everything. Take that piece of RNA. An intuitive mental model is that it's some form of "instruction" or a bunch of instruction, isn't it? It's also wrong, because it just encodes a protein that acts the way it does only because of its shape (that is, one of its potential energy local minimums) and the shape of other proteins around it. That shape is only weakly local, it can be affected by far-away sections of peptide sequence. So it's almost impossible to systematically break it down, you have to consider and model things as a whole , which is insanely complex both computationally and cognitively. If you want a good mental model of how it works, imagine you assemble a thing from metal balls and springs. You take a few thousands balls and connect most of them with springs of different strengths. You then take this thing and throw it on the floor; it will assume a shape that is implicitly encoded in spring strengths, its environment, and the way you've assembled it. You can even make it change shape if you poke on it the right way. That's how biology works in a nutshell; it's a nightmare to design anything for systems like that. Again, you can't simplify and break down and encapsulate and abstract like you do in programming.
• 6nf 6y ago
  Protein folding is not solved, that headline was overstating the actual achievement by Google's protein folding solution.
• zero_deg_kevin 6y ago
  Because the problem is significantly more complicated than sequencing and folding.
• asdff 6y ago
  Because it's a harder problem than it seems at face value.