6 ms·

Relevant XKCD: http://xkcd.com/1605/ http://xkcd.com/1605/

by FreakyT 11y ago

dnautics 11y ago
The problem with DNA 'source code' is not that it's hard to read, it's that we don't fully know how to read it. Yes, we know what protein sequence comes out but the chemical consequences are not particularly well known. With google's source code, you could, in theory, look at it long enough and have a working understanding down to the level of electrons moving around specific spots in the chips in the Google datacenter. As a professional (wet) biochemist and also a coder, my personal feeling is that biology is much, much shallower. However, the knowledge required is broader but incomplete. If you're trying to, say optimize an enzyme, beyond molecular biology, you'd do well to incorporate knowledge from biochemistry (is this an active site amino acid? Maybe I shouldn't touch it. What sort of yield changes can I expect if this enzyme catalyzes the rate-determining step vs. not), cell biology (will adding this amino acid sequence send it to the wrong compartment?), biophysics (will changing this residue mess up the protein fold?), electrochemistry (is the electrical potential of this iron-sulfur cluster consistent with the process I want?) etc etc. A lot of 'biohackers' are script kiddies that just ctrl-c/ctrl-v gene sequences and hope that it works. That's why you see a lot of gene synthesis companies claim a offer of "codon optimizing" a gene. It's something that sounds hard, sounds critical, and gets something done. The rest of it is much, much harder, and requires actual thought.
- bduerst 11y ago
  Genome is easy to read, proteonome is hard to understand. We have a good grasp on protein folding, but we're not to the point where we can fully synthesize proteins from raw genetic sequences. It would be great if we could get there in our lifetime.
- pazimzadeh 11y ago
  I'm not sure I understand what you mean when you say that "biology is much, much shallower". Shallower than what, and in what way? What might it look like if it were deeper?
  - silentplummet 11y ago
    When we use a computer programming language, we are directing an abstract machine to interpret and manipulate data to get a result that we want. We have all the knowledge we need about the machine because we conceived and designed it ourselves. DNA is like a programming language for a biological computer, a living cell. However, we don't know nearly everything there is to know about a living cell. We can't predict its mechanisms. There is no debugger. The compiler didn't come with an instruction manual. The code bootstraps itself into its own machine and runs in an environment we can't predict. And the syntax has been obfuscated and optimized by a genetic algorithm that's been running in parallel on quintillions of cores for a billion years. Because the code executes on an unknown machine in an unpredictable physical environment, many features we might expect to see in a programming language are missing. This might be what he meant by "shallow".
    - eli_gottlieb 11y ago
      >DNA is like a programming language for a biological computer, a living cell. However, we don't know nearly everything there is to know about a living cell. We can't predict its mechanisms. There is no debugger. The compiler didn't come with an instruction manual. The code bootstraps itself into its own machine and runs in an environment we can't predict. And the syntax has been obfuscated and optimized by a genetic algorithm that's been running in parallel on quintillions of cores for a billion years. And, just to finish off, the machine is stochastically nondeterministic.
    - pazimzadeh 11y ago
      > Because the code executes on an unknown machine in an unpredictable physical environment, many features we might expect to see in a programming language are missing. This might be what he meant by "shallow". Without knowing how much more there is to know about biology, how can we expect to see certain features or not? What about tasks that are supremely efficient in biology but resource intensive "in silico"? I'm having a hard time fathoming biology as shallow in any way. The fact that it's bootstrapped and live, that you don't get to restart the computer or cut the flow of information makes it all the less shallow to me, unless I'm misunderstanding how that word was used.
- vectorjohn 11y ago
  Nobody said it was hard to read. The comic you're replying to certainly didn't say that. I disagree that you could look at Google's source code and know much about the data center. You would have to have a lot more knowledge about infrastructure which is completely hidden from you. And that's about where we are with proteins. We can figure out the protein, and then try to simulate what it would do, but it's not easy or straight forward. So your analogy with Google source code would be like, you could simulate what a data center might be like, but you're just guessing and could be way off. I think the point of the comic is that if you look at Google source code, it's NOT straight forward to understand. You can read it, sure. Anyone can read an operating system worth of assembly, too. But knowing what it does, that's a hard problem (without running it). And that Google's code is only a few years of optimization by people trying to keep the code comprehensible instead of billions of years of optimization with no care for readability or organization.
bobcostas55 11y ago
Evolution as optimization process has a lot of problems though. Most importantly, it's optimizing for fitness. As Richerson & Boyd memorably put it, "All animals are under stringent selection pressure to be as stupid as they can get away with." Fitness is not necessarily something we're interested in. Second, evolution is susceptible to getting caught in local maxima/minima. Though it's hard to argue that we could engineer ourselves to a higher peak, because we can't really see any other peaks at the moment.
- tdaltonc 11y ago
  There are some obvious things to "fix" in humans if we knew how. The laryngeal nerve, the mechanics of birth, the growth rate of cartilage. Certainly it's possible to be hubristic here, but there's also just as clearly some things that need fixing.
- eli_gottlieb 11y ago
  We're not really in a peak or valley of any kind at the moment. If evolution pushed us to a zero-point in the derivative of any kind of imaginary fitness function, it was probably a saddle point in which some mutations fall right off and others could rise high but would require more environmental resources. But otherwise we should assume that zeroes in the derivative are uncommon, and thus we're probably not at one.
  - bobcostas55 11y ago
    My point is not that we're at the exact top, but that we might be near the top of a hill when there's a mountain next to it. Evolution isn't going to go down the hill to climb up the mountain, but an engineer might eventually be able to do it.

Relevant XKCD: http://xkcd.com/1605/ http://xkcd.com/1605/

by FreakyT 11y ago

Relevant XKCD: http://xkcd.com/1605/ http://xkcd.com/1605/

The problem with DNA 'source code' is not that it's hard to read, it's that we don't fully know how to read it. Yes, we know what protein sequence comes out but the chemical consequences are not particularly well known. With google's source code, you could, in theory, look at it long enough and have a working understanding down to the level of electrons moving around specific spots in the chips in the Google datacenter. As a professional (wet) biochemist and also a coder, my personal feeling is that biology is much, much shallower. However, the knowledge required is broader but incomplete. If you're trying to, say optimize an enzyme, beyond molecular biology, you'd do well to incorporate knowledge from biochemistry (is this an active site amino acid? Maybe I shouldn't touch it. What sort of yield changes can I expect if this enzyme catalyzes the rate-determining step vs. not), cell biology (will adding this amino acid sequence send it to the wrong compartment?), biophysics (will changing this residue mess up the protein fold?), electrochemistry (is the electrical potential of this iron-sulfur cluster consistent with the process I want?) etc etc. A lot of 'biohackers' are script kiddies that just ctrl-c/ctrl-v gene sequences and hope that it works. That's why you see a lot of gene synthesis companies claim a offer of "codon optimizing" a gene. It's something that sounds hard, sounds critical, and gets something done. The rest of it is much, much harder, and requires actual thought.

bduerst 11y ago
Genome is easy to read, proteonome is hard to understand. We have a good grasp on protein folding, but we're not to the point where we can fully synthesize proteins from raw genetic sequences. It would be great if we could get there in our lifetime.
pazimzadeh 11y ago
I'm not sure I understand what you mean when you say that "biology is much, much shallower". Shallower than what, and in what way? What might it look like if it were deeper?
- silentplummet 11y ago
  When we use a computer programming language, we are directing an abstract machine to interpret and manipulate data to get a result that we want. We have all the knowledge we need about the machine because we conceived and designed it ourselves. DNA is like a programming language for a biological computer, a living cell. However, we don't know nearly everything there is to know about a living cell. We can't predict its mechanisms. There is no debugger. The compiler didn't come with an instruction manual. The code bootstraps itself into its own machine and runs in an environment we can't predict. And the syntax has been obfuscated and optimized by a genetic algorithm that's been running in parallel on quintillions of cores for a billion years. Because the code executes on an unknown machine in an unpredictable physical environment, many features we might expect to see in a programming language are missing. This might be what he meant by "shallow".
  - eli_gottlieb 11y ago
    >DNA is like a programming language for a biological computer, a living cell. However, we don't know nearly everything there is to know about a living cell. We can't predict its mechanisms. There is no debugger. The compiler didn't come with an instruction manual. The code bootstraps itself into its own machine and runs in an environment we can't predict. And the syntax has been obfuscated and optimized by a genetic algorithm that's been running in parallel on quintillions of cores for a billion years. And, just to finish off, the machine is stochastically nondeterministic.
  - pazimzadeh 11y ago
    > Because the code executes on an unknown machine in an unpredictable physical environment, many features we might expect to see in a programming language are missing. This might be what he meant by "shallow". Without knowing how much more there is to know about biology, how can we expect to see certain features or not? What about tasks that are supremely efficient in biology but resource intensive "in silico"? I'm having a hard time fathoming biology as shallow in any way. The fact that it's bootstrapped and live, that you don't get to restart the computer or cut the flow of information makes it all the less shallow to me, unless I'm misunderstanding how that word was used.
vectorjohn 11y ago
Nobody said it was hard to read. The comic you're replying to certainly didn't say that. I disagree that you could look at Google's source code and know much about the data center. You would have to have a lot more knowledge about infrastructure which is completely hidden from you. And that's about where we are with proteins. We can figure out the protein, and then try to simulate what it would do, but it's not easy or straight forward. So your analogy with Google source code would be like, you could simulate what a data center might be like, but you're just guessing and could be way off. I think the point of the comic is that if you look at Google source code, it's NOT straight forward to understand. You can read it, sure. Anyone can read an operating system worth of assembly, too. But knowing what it does, that's a hard problem (without running it). And that Google's code is only a few years of optimization by people trying to keep the code comprehensible instead of billions of years of optimization with no care for readability or organization.

bobcostas55 11y ago

Evolution as optimization process has a lot of problems though. Most importantly, it's optimizing for fitness. As Richerson & Boyd memorably put it, "All animals are under stringent selection pressure to be as stupid as they can get away with." Fitness is not necessarily something we're interested in. Second, evolution is susceptible to getting caught in local maxima/minima. Though it's hard to argue that we could engineer ourselves to a higher peak, because we can't really see any other peaks at the moment.

tdaltonc 11y ago
There are some obvious things to "fix" in humans if we knew how. The laryngeal nerve, the mechanics of birth, the growth rate of cartilage. Certainly it's possible to be hubristic here, but there's also just as clearly some things that need fixing.
eli_gottlieb 11y ago
We're not really in a peak or valley of any kind at the moment. If evolution pushed us to a zero-point in the derivative of any kind of imaginary fitness function, it was probably a saddle point in which some mutations fall right off and others could rise high but would require more environmental resources. But otherwise we should assume that zeroes in the derivative are uncommon, and thus we're probably not at one.
- bobcostas55 11y ago
  My point is not that we're at the exact top, but that we might be near the top of a hill when there's a mountain next to it. Evolution isn't going to go down the hill to climb up the mountain, but an engineer might eventually be able to do it.