7 ms·

It's almost unbelievable how DNA seems to "just work". DNA from one organism breaking apart and slipping into another somehow leads to shared expressions across

• throwanem 5y ago
  Don't try to think about genomics in programming terms. At best you'll only confuse yourself; at worst, others also. Both a computer program and a genome encode information, but that's about where the similarities end.
  • inigojonesguy 5y ago
    >Don't try to think about genomics in programming terms. At some point, some Newton person will figure it. It always happen. As for now, it might be interesting to understand why exactly the analogy between genomics and programming fails. It might bring interesting insights into both fields. So why not try to think about?
    • throwanem 5y ago
      Because the only way to imagine a useful comparison between these fields can be made is to be profoundly ignorant of at least one of them.
      • burning_hamster 5y ago
        As a bioinformatician, I cannot wait to use this quote on someone.
        • throwanem 5y ago
          As an enthusiastically former staff engineer at a bioinformatics institute, I'm happy to have been of help! Please feel free to do so without attribution; if nothing else, it'd be a shame at this late date to have my opinions of the caste system in academia disturbed by the novel experience of receiving credit for my contributions to the work of people with letters after their names. :D
          • airhead969 5y ago
            Department chairs > PIs >~ profs > visiting profs > assistant profs >~ visiting asst profs > postdocs > grad students > employees > undergrads > high-school interns Dedicated grant-writing staff are gold, literally and figuratively. (I worked at a biomedical informatics shop.)
      • sooheon 5y ago
        Rather than assert the negative, can you state some positive facts about one or the other that makes this point clear?
        • throwanem 5y ago
          Software changes over spans of minutes to decades; genomes change over spans of millions of years. Software is written; genomes are not. The complexity of software is constrained by programmers' ability to comprehend it; the complexity of genomes is not. The environment in which software functions is determined by humans; the environment in which genomes function is not.
          • sooheon 5y ago
            Those are trivial surface level differences relative to the central idea of encoding, storing, replicating, editing digital information, which interfaces with other digital and analog systems.
            • throwanem 5y ago
              Not that there's much point to saying so, since you appear to be here for no other reason than to assert that my argument is false because you would prefer it be so, but here's another: software is digital; genomes are not.
              • staticassertion 5y ago
                FWIW all of these differences still feel extremely surface level. I'm no expert but I certainly am, so far, aware of everything you've said with regards to how they differ - I'm kinda hoping for more, given the strong assertion you made that one can not relate the two without being fundamentally ignorant of either topic. I also think it's somewhat ironic that you're accusing them of only being here to say "you're wrong" but that's what you've done in this thread? I only bring this up because I think we're all after the same thing here - to understand an incredibly interesting topic. I suspect most of us are really here to learn and discuss. You seem like you have a background in the area, I'm sure we would all benefit from learning about the differences. If it's the case that the similar is that DNA and code both encode information, and the differences are based on how they do so, it's hard to see why you think they can't be related at all. You've been relating the two.
      • techbio 5y ago
        I love this. It's a little black and white, but the comparison is as between video game worlds and the real world. Only enough to fool the willing eye. I use a variation of this form as 'persons whos science and religions conflict don't know enough about either one'.
      • dekhn 5y ago
        I'm profoundly ignorant in neither (PhD in biophysics, software engineer for 20 years). Genomics and programming analogies are cool, but the most important thing is that understanding that molecular structures can encode information in a replicable way, and the discovery of application of entropy to data storage and transmission, demonstrates that information is a universal concept, that the genome is a data storage system, and the enzymes that operate it are operating on information, in a computational way. To me that's a pretty useful comparison.
  • staticassertion 5y ago
    I can only use the models that I have, accurate or otherwise. I hope I'm not confusing others, I'm not pretending to be an expert in DNA. > Both a computer program and a genome encode information, but that's about where the similarities end. FWIW this is a very significant similarity to me.
    • throwanem 5y ago
      One might with equal merit say that, because I know English orthography, I can also read Linear A.
      • staticassertion 5y ago
        I'm not sure what it is you think I'm trying to say, but much of your point seems to be "don't talk about things you don't understand", which I have no interest in abiding. I like talking about things I don't understand, and I've enjoyed the posts from you and others on the topic, even if I'll only ever be a layman.
        • throwanem 5y ago
          Talking about things you don't understand is no problem by me! What I'm trying to point to here is the hazard of making assumptions about something one doesn't understand, and then trying to reason about the thing based on those assumptions.
          • staticassertion 5y ago
            Oh sure, yeah I mean it's all in good fun. I wouldn't try to actually establish any serious thought other than "this is wild".
      • faeyanpiraat 5y ago
        I think a working analogy here would be that source code (dna) gets compiled (physics/chemistry) into an executable (living organism with even more dna) which gets executed by the os (phys/chem again) to produce changes on some data (organism interacts with the environment), and on and on.. The details are of course endless and they aren’t interchangeable between the two fields, but the analogy is still there..
  • uhhhhhhhhhhhhhh 5y ago
    So when DNA gets pushed through a ribosome and the base pairs are used as instructions to build proteins that is not computation? Sounds turingmachine (or at least, machinelike) to me
• deleted 5y ago
  [deleted]
• tachyonbeam 5y ago
  > It's like taking a random byte sequence from some binary, shoving it randomly into another, and the new binary gets useful new features. If you think about it for a moment, our genetic code is kind of designed to work that way. You get half of your genetic code from your mom, the other half from your dad, and somehow, all of these genes "just work" together. It's kind of miraculous when you think that there are very many genes that encode how your brain works, and how your liver works, your muscles, etc. Somehow, provided the baby can be born, a mishmash of genes from two different individuals almost always works out.
  • dalmo3 5y ago
    > all of these genes "just work" together That's a little bit tautological since if the genes didn't work together they wouldn't be here after all these years, right? Fascinating nonetheless.
    • sooheon 5y ago
      That seems to be the point the parent is making. Tautology is the the only way we can explain the way life happens to be -- it's because it's advantageous for it to be that way.
    • Blikkentrekker 5y ago
      It should also be pointe out that about two thirds of human conceptions result into early embryonic death, so evidently it is not as smooth a ride as suggested.
  • walleeee 5y ago
    I'm just picking nits, but :%s/designed/evolved/g Do very much agree it's miraculous. Biological organisms are robust to error and chance in ways no designed system comes close to matching. It's awe-inspiring
    • VeninVidiaVicii 5y ago
      In genetics it’s very common to say that things are designed a certain way without invoking a creator.
• TheEzEzz 5y ago
  This is crazy from the perspective of "old fashioned binaries", but less so in the context of neural networks. You can do all sorts of splicing and dicing of the bits in neural networks (their weights) and end up with useful networks. Dropout, for example, specifically trains a network to be resilient to having swaths of the network removed, and makes individual features in the network resilient to having a random selection of other features present or not-present. If I remember right, the original dropout paper even analogizes this to how genes have evolved to be resilient to this type of random pairing.
• kbenson 5y ago
  It's less so when you know about some evolutionary programming techniques, such as using Lisp with a subset of the code that defines behavior in a tree structure that allows for parts of that tree to be swapped in and out from other programs using the same design whike still yielding an executing program. Combined with a fitness function you can "breed" programs for a task. As I understand it there are attributes of Lisp and attributes of the program structure (such as putting much of the logic in that tree structure with defined split points) which makes this much more feasible than otherwise. My guess is that DNA has evolved similarly, where the ways in which it splits and the mechanism in which it is interpreted and executed help, and also the organisms we're talking about (us and the other complex ones) have iterated to a design that's more amenable to bits being swapped. That is large chunks of us may be more similar to a lisp program with attributes that make it easy to swap parts than to a bunch of object bytecode with absolute and relative jumps all over. Note: A lot of this is poorly remembered from a survey of AI class two decades ago, so it bears someone with a stronger background verifying I'm not making a complete hash of it.
• echelon 5y ago
  I think the binary example is incredibly poor and makes understanding this much harderr. Genes code for proteins (and promoters, etc.) and wind up in a chemical soup in flux. They're going to bounce around and do things. Their presence will be more akin to new kinds of cars or trucks entering a highway, and they'll have different impacts to traffic (kinetics, thermodynamics).
• andrewflnr 5y ago
  The closest programming analogy for a new gene is probably dropping a new listener/sender on a message bus. It can send messages independently in response to messages that were already on the bus before it arrived. If there's a little bit of a shared language (which there is here, since the bus is chemistry itself), that can lead to new behaviors of the system without necessarily breaking anything.
• vikingerik 5y ago
  Well, survivorship bias. We only see the results where it worked, we don't see the enormous number of attempts where it didn't.
• Dylan16807 5y ago
  A program has to run those sequences mostly in order. Rather than swapping around blobs of binary it's more like each gene being its own small program, and things working is much less surprising in that context.
• Rapzid 5y ago
  What I'm very interested in ATM(just now after reading this topic) is how the process of evolution really works. Not the selection so much, but the actual mutations. The last I ever learned about it, and perhaps the common belief, is that random-ish gene mutations account for it. 4 billion years doesn't seem like enough time to account for all that unless changes are heavily weighted towards doing something somewhat useful. Like there is a system at play.. Lego blocks vs bits. IDK.
  • idiotsecant 5y ago
    4 billion years is a very, very, very long time.
    • Rapzid 5y ago
      Yeah but 4 billion is nothing when talking about a measly 256bit space, much less a 3 million base DNA strand.
  • throwamon 5y ago
    If you think evolution is just selection and mutations, I can see how you'd think it's not enough (even though selection is usually a very strong force that "locks good mutations in place", which can create a compounding effect in chances of an organism's fitness, so a long time of mutations + locking good ones in place should be almost enough to convince you if you do the math). It's been some time since I studied this so I'm just going to write whatever comes to mind. Maybe a key part of what's missing in your understanding is not so much "micro" genetics but biogeography and population genetics. You'd also want to check simulations and comparisons with real-world data on some models to see how a population evolves to see that it "really works". It's important to understand that there are different models, and for each one there's a set of "forces" and important parameters. The bigger picture is, it's the whole interplay between mutation, selection, genetic drift, gene flow; things like differences in population size over time and space, migrations, isolation and reconnection, etc. that makes it work. You might also want to take a look into genetic/functional/morphological modularity. I've just skimmed these articles, but they seem relevant: https://www.nature.com/articles/hdy2010136 https://www.nature.com/articles/hdy2010136 https://www.nature.com/scitable/knowledge/library/natural-selection-genetic-drift-and-gene-flow-15186648/ https://www.nature.com/scitable/knowledge/library/natural-se... There's much more but my memory is murky. Ideally you would want to take a course or read a textbook on evolution. A few popsci books are ok (Dawkins, E. O. Wilson). TLDR: What the other commenter said -- 4 billion years is a very, very, very long time.