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Are there any works consumable by a layperson that explore the mathematical probabilities of evolution and genetic diversity? When you look at it from the pers

by jcims 5y ago

Are there any works consumable by a layperson that explore the mathematical probabilities of evolution and genetic diversity? When you look at it from the perspective of simple combinatorics, nothing seems possible. A single gene has say 4^300 permutations. You could devote the entire mass of the known universe iterating on versions of a protein a trillion times per second for a trillion years and not even remotely scratch the surface of possible configurations.

KhoomeiK 5y ago
I think you might be severely underestimating the level of parallelization happening in living beings. There are 100 trillion bacteria in every single human. Extrapolated to the number of bacteria on the planet, that's a whole lot of computational ability.
- Retr0id 5y ago
  I think you're severely underestimating 4^300. The answer to GP's question is that it's not an iterative brute-force. But I'm not a biologist, so I can't go into any more detail...
  - deleted 5y ago
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  - gus_massa 5y ago
    I think it's more important that it's a branch-and-prune algorithm. Many branches are created, but they are quickly pruned if they are worse or just unlucky. (Someone may be a the "best" human alive, but if a piano falls on the head, s/he ded and pruned.) Branches are retried, so if some branch is an improvement and is cut by bad luck, it may be luckier a few million years later. This does not guarantee that the "best" solution is found, but also avoid looking in the 4^300 combinations. Also, there are shorter genes, some proteins have ~50 amino acids (~150 bases), and some useful short amino acids chains have a length of 20 or even less (~60 bases or less). It's possible to start with a short versions that does something slightly useful, and slowly increase the length an efficiency.
    - jcims 5y ago
      The 'branch-and-prune' aspect of evolution seems to be the primary lifeline out of the combinatorics conundrum.
Zamicol 5y ago
I found the programmer.
ramraj07 5y ago
Look up the Logic of Chance by Eugene Koonin. Written by an actual evolution researcher of current times instead of legacy hacks like you-know-who. This book is even better because it actually talks a lot of about horizontal gene transfer s role in prokaryotic evolution, and borgs might actually be something involved in a similar process. Kinda prescient if you ask me!
- jcims 5y ago
  Looked perfect so I just bought the paperback, thank you!
- RealityVoid 5y ago
  I am a layperson, so I would be really curious as to whom this one that is known is.
  - ramraj07 5y ago
    Richard Dawkins of course!
mrtnmcc 5y ago
A single neural network with 8 bit weights and 1M parameters has 256^1000000 possibilities by that logic, but we can train it fine with simple evolutionary algorithms like SPSA (Simultaneous perturbation stochastic approximation) E.g., https://openai.com/blog/evolution-strategies/ https://openai.com/blog/evolution-strategies/ One of the remarkable results is that convergence rate for each parameter is not strongly dependent on the number of parameters.
- jcims 5y ago
  Sure, but we can't really explain why that works either can we? However, I would suggest that there's a difference in evolution. With the neural networks we train, there is actually a highly engineered process required to create the state in which a network can be trained and inferences be driven through it. The necessary combination of hardware that is able to perform and persist operations on information and the algorithms required to do so in a way to yield this outcome is an extremely complex set of pre-conditions that we wouldn't expect to find in the computing equivalent of a primordial soup. With natural evolution, there is no obvious agency or intent behind it. Who is there to care whether or not life started on Earth, and/or who is driving the laws of nature such that the constructive, generative process of genetic evolution actually 'works' as well as it does? Seemingly nobody. Yet this process is able to create systems that operate on scales that we can only dream of. Look up YouTube videos on ATP Synthase for example. It's a nanomachine in every sense of the word. It uses the proton equivalent of a water wheel to spin a little machine that grabs a molecule of ADP, a molecule of inorganic phosphate, then literally snaps them together with mechanical leverage to make ATP. This little miracle machine that powers most of life on earth was built in literal and figurative darkness...it's so damn small light can't see it, and there was nobody there to appreciate its beauty until we came along billions of years later. Ultimately I'm not surprised natural evolution works, I'm surprised at its speed and efficacy.
  - mtqwerty 5y ago
    This is an insightful comment but I think you’re missing one thing in your understanding of natural evolution. Evolution has a “reward function” and it’s survival of the fittest. As reproduction produces different variants of the same organism, some variations help the organism while others do not. Organisms with the helpful mutations will be more likely to pass those onto their offspring. Organisms with detrimental variations will be less likely to pass those variations to their kids. It’s not a precise process like gradient descent but when there are billions (trillions?) of organisms evoking simultaneously and independently, it makes more sense how the complexity of biology has come about.
andreskytt 5y ago
Three factors, I think, might be at play: 1. Parallelism. The number of all sorts of organisms going through mutations is large. Like 10^40 kind of large. 2. Time. This has been going on at a very rapid tempo for quite a while. 3. Evolutionary pressure. In every generation, harmful mutations are radically weeded out so your search space is dramatically reduced at each generation. While the first two could be roughly estimated, the third one involves non-linearity very sensitive to estimation errors. So I don’t think anybody can _prove_ this is how we ended up with Angela Merkel but it’s not implausible either and nobody has a better idea
deleted 5y ago
[deleted]
turingcomplet 5y ago
Dawkins talks about this in The Blind Watchmaker, calling it cumulative selection (not sure where else this term is used). It's hard to wrap my head around, but that also makes sense given that our intuition is not adapted for such large numbers. Considering how long the time scale is, how many mutations are discarded, the driving force of survival, and probably other factors I'm forgetting, it's not that surprising we end up with a small (relative to the combinatorial possibilities) number of configurations. But again, I do still feel like I'm trying to convince myself right now, even though when I read the (better written) explanations, it makes sense in that moment.
dri_ft 5y ago
Dennett talks about this sort of thing in broad outline in Darwin's Dangerous Idea, which is aimed at the layperson (though fairly dense and demanding). I'm not sure if it's mathematically detailed enough for what you seek, but it might be worth a look.
elzr 5y ago
I think you'll enjoy Andreas Wagner's 2014 Arrival of the Fittest https://amzn.com/B00INIQTA6 https://amzn.com/B00INIQTA6 The title is of course a play on the (in)famous phrase "survival of the fittest". The book's about how nature manages to actually explore the vast, vast genetic space and harvest its bounties cumulatively, while under the constrain that every "step" must be a viable organism with offspring.
jryb 5y ago
I'm sure the readings that other people linked will be useful, but two points to give some intuition: 1. Genes don't have to be optimal, or even close to optimal to work. They just have to be good enough. 2. Nature loves to copy. Large segments of DNA can be copied by a number of mechanisms and randomly placed elsewhere in a genome. So once nature "discovers" (for example) a DNA-binding motif, that motif can be added to other genes, and now you have a diverse set of DNA-binding proteins, which will continue evolving on their own.

by jcims 5y ago

KhoomeiK 5y ago

I think you might be severely underestimating the level of parallelization happening in living beings. There are 100 trillion bacteria in every single human. Extrapolated to the number of bacteria on the planet, that's a whole lot of computational ability.

Retr0id 5y ago
I think you're severely underestimating 4^300. The answer to GP's question is that it's not an iterative brute-force. But I'm not a biologist, so I can't go into any more detail...
- deleted 5y ago
  [deleted]
- deleted 5y ago
  [deleted]
- gus_massa 5y ago
  I think it's more important that it's a branch-and-prune algorithm. Many branches are created, but they are quickly pruned if they are worse or just unlucky. (Someone may be a the "best" human alive, but if a piano falls on the head, s/he ded and pruned.) Branches are retried, so if some branch is an improvement and is cut by bad luck, it may be luckier a few million years later. This does not guarantee that the "best" solution is found, but also avoid looking in the 4^300 combinations. Also, there are shorter genes, some proteins have ~50 amino acids (~150 bases), and some useful short amino acids chains have a length of 20 or even less (~60 bases or less). It's possible to start with a short versions that does something slightly useful, and slowly increase the length an efficiency.
  - jcims 5y ago
    The 'branch-and-prune' aspect of evolution seems to be the primary lifeline out of the combinatorics conundrum.

Zamicol 5y ago

I found the programmer.

ramraj07 5y ago

Look up the Logic of Chance by Eugene Koonin. Written by an actual evolution researcher of current times instead of legacy hacks like you-know-who. This book is even better because it actually talks a lot of about horizontal gene transfer s role in prokaryotic evolution, and borgs might actually be something involved in a similar process. Kinda prescient if you ask me!

jcims 5y ago
Looked perfect so I just bought the paperback, thank you!
RealityVoid 5y ago
I am a layperson, so I would be really curious as to whom this one that is known is.
- ramraj07 5y ago
  Richard Dawkins of course!

mrtnmcc 5y ago

A single neural network with 8 bit weights and 1M parameters has 256^1000000 possibilities by that logic, but we can train it fine with simple evolutionary algorithms like SPSA (Simultaneous perturbation stochastic approximation) E.g., https://openai.com/blog/evolution-strategies/ https://openai.com/blog/evolution-strategies/ One of the remarkable results is that convergence rate for each parameter is not strongly dependent on the number of parameters.

jcims 5y ago
Sure, but we can't really explain why that works either can we? However, I would suggest that there's a difference in evolution. With the neural networks we train, there is actually a highly engineered process required to create the state in which a network can be trained and inferences be driven through it. The necessary combination of hardware that is able to perform and persist operations on information and the algorithms required to do so in a way to yield this outcome is an extremely complex set of pre-conditions that we wouldn't expect to find in the computing equivalent of a primordial soup. With natural evolution, there is no obvious agency or intent behind it. Who is there to care whether or not life started on Earth, and/or who is driving the laws of nature such that the constructive, generative process of genetic evolution actually 'works' as well as it does? Seemingly nobody. Yet this process is able to create systems that operate on scales that we can only dream of. Look up YouTube videos on ATP Synthase for example. It's a nanomachine in every sense of the word. It uses the proton equivalent of a water wheel to spin a little machine that grabs a molecule of ADP, a molecule of inorganic phosphate, then literally snaps them together with mechanical leverage to make ATP. This little miracle machine that powers most of life on earth was built in literal and figurative darkness...it's so damn small light can't see it, and there was nobody there to appreciate its beauty until we came along billions of years later. Ultimately I'm not surprised natural evolution works, I'm surprised at its speed and efficacy.
- mtqwerty 5y ago
  This is an insightful comment but I think you’re missing one thing in your understanding of natural evolution. Evolution has a “reward function” and it’s survival of the fittest. As reproduction produces different variants of the same organism, some variations help the organism while others do not. Organisms with the helpful mutations will be more likely to pass those onto their offspring. Organisms with detrimental variations will be less likely to pass those variations to their kids. It’s not a precise process like gradient descent but when there are billions (trillions?) of organisms evoking simultaneously and independently, it makes more sense how the complexity of biology has come about.

andreskytt 5y ago

Three factors, I think, might be at play: 1. Parallelism. The number of all sorts of organisms going through mutations is large. Like 10^40 kind of large. 2. Time. This has been going on at a very rapid tempo for quite a while. 3. Evolutionary pressure. In every generation, harmful mutations are radically weeded out so your search space is dramatically reduced at each generation. While the first two could be roughly estimated, the third one involves non-linearity very sensitive to estimation errors. So I don’t think anybody can _prove_ this is how we ended up with Angela Merkel but it’s not implausible either and nobody has a better idea

deleted 5y ago

[deleted]

turingcomplet 5y ago

Dawkins talks about this in The Blind Watchmaker, calling it cumulative selection (not sure where else this term is used). It's hard to wrap my head around, but that also makes sense given that our intuition is not adapted for such large numbers. Considering how long the time scale is, how many mutations are discarded, the driving force of survival, and probably other factors I'm forgetting, it's not that surprising we end up with a small (relative to the combinatorial possibilities) number of configurations. But again, I do still feel like I'm trying to convince myself right now, even though when I read the (better written) explanations, it makes sense in that moment.

dri_ft 5y ago

Dennett talks about this sort of thing in broad outline in Darwin's Dangerous Idea, which is aimed at the layperson (though fairly dense and demanding). I'm not sure if it's mathematically detailed enough for what you seek, but it might be worth a look.

elzr 5y ago

I think you'll enjoy Andreas Wagner's 2014 Arrival of the Fittest https://amzn.com/B00INIQTA6 https://amzn.com/B00INIQTA6 The title is of course a play on the (in)famous phrase "survival of the fittest". The book's about how nature manages to actually explore the vast, vast genetic space and harvest its bounties cumulatively, while under the constrain that every "step" must be a viable organism with offspring.

jryb 5y ago

I'm sure the readings that other people linked will be useful, but two points to give some intuition: 1. Genes don't have to be optimal, or even close to optimal to work. They just have to be good enough. 2. Nature loves to copy. Large segments of DNA can be copied by a number of mechanisms and randomly placed elsewhere in a genome. So once nature "discovers" (for example) a DNA-binding motif, that motif can be added to other genes, and now you have a diverse set of DNA-binding proteins, which will continue evolving on their own.