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Insect Has Gears in Its Legs (2013)

nationalgeographic.com

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Re: Insect Has Gears in Its Legs (2013)

#31

Post by mindfulplay »

Truly fascinating. It makes me wonder how such a thing could be encoded inside a DNA.

As in, is there a field of study similar to computer science/information theory on certain fundamental biological "laws of transformation"?

Say, we have six billion or so pairs in the DNA. How could a series of transformations from those pairs with other proteins produce this complexity especially ones that requires a particular 3d shape, time based mechanisms and reactions all tied together efficiently and passed from generation to generation?

Obviously perhaps not a "designed by some magical entity", but six billion pairs/nibbles seem quite magical to encode this complexity... It is certainly hard to study this even over many decades, but I wonder if there are certain fundamental laws or units or theories that help provide pathways to understand such transformations.

Re: Insect Has Gears in Its Legs (2013)

#32

Post by cosmodisk »

chmod775 wrote: post #21
csomar wrote: post #18

Earlier quoted context omitted.

Actually it's the human bodies that are quite wasteful (so are humans themselves). Many big animals can keep going without food for months. And it's not just their oily fat reserves, they are much more efficient with energy.

Humans are just better at other things. Like problem solving. A big brain takes a lot of energy. Plus human bodies aren't all that terrible: https://www.wikiwand.com/en/Persistence_hunting

Also at hunting. We have no competition in this area.

Re: Insect Has Gears in Its Legs (2013)

#33

Post by core-questions »

mindfulplay wrote: post #31

Truly fascinating. It makes me wonder how such a thing could be encoded inside a DNA. As in, is there a field of study similar to computer science/information theory on certain fundamental biological "laws of transformation"? Say, we have six billion or so pairs in the DNA. How could a series of transformations from those pairs with other proteins produce this complexity especially ones that requires a particular 3d…

I think we're still a generation or so away from getting to this level. Fundamentally, though, it doesn't seem to be too wild of a suggestion that DNA is going to end up looking like an incredibly complex, incredibly hacky computer program, utilizing every last potential possibility of its mechanical substrate.

Think about demoscene or 80s video game programming, tight little assembly routines by developers that did not care anywhere near as much about simple and clear code, security, portability, or anything else as they did about raw performance. Analyzing some of these after the fact (not that I've done it, but I've read the stories of people doing it) seems to be every bit as difficult as being able to do it in the first place. And this is something that _is_ the product of intelligent design; when raw evolution is responsible for the work, it's even less liable to make some kind of logical sense when viewed at the lowest level. The emergent effect of random change (and its impact on reproductive fitness) is the only thing that matters.

Now, consider this: scientists analyzing a simple processor can't even tell you how it works, using modern equipment:

https://journals.plos.org/ploscompbiol/article?id=10.1371/jo...

> we take a classical microprocessor as a model organism, and use our ability to perform arbitrary experiments on it to see if popular data analysis methods from neuroscience can elucidate the way it processes information. Microprocessors are among those artificial information processing systems that are both complex and that we understand at all levels, from the overall logical flow, via logical gates, to the dynamics of transistors. We show that the approaches reveal interesting structure in the data but do not meaningfully describe the hierarchy of information processing in the microprocessor. This suggests current analytic approaches in neuroscience may fall short of producing meaningful understanding of neural systems, regardless of the amount of data.

What do we take from that? It seems to me that our current understanding of DNA is extremely crude, and that we're still a few breakthroughs away from understanding any moderate to large scale 'logical structure' in it.

Re: Insect Has Gears in Its Legs (2013)

#34

Post by brundolf »

miked85 wrote: post #30
wallacoloo wrote: post #27

Earlier quoted context omitted.

Just use your browser’s “reader mode”. Seems to get around this style of popup pretty easily (at least on safari and usually Firefox too).

Normally I do that - in this case, pictures are useful though.

Usually pictures remain visible in reader mode

Re: Insect Has Gears in Its Legs (2013)

#35

Post by throwanem »

curryst wrote: post #15
Conlectus wrote: post #14

Earlier quoted context omitted.

It seems to me this "impossibility" might be an artifact of definition: if some system contains disjoint parts, we no longer call it "an animal". Colonial animals are the edge case here. Most would be hesitant to say an ant colony is "an animal", but are happy to refer to a Portuguese Man 'o' War as such, despite also being a colony.

All members of a colonial animal are genetically identical, which I believe is why a man of war is an animal but an ant colony is a society. I don't think ants are genetically identical, although I'm not certain. Man o Wars are also not disjoint. They have specialized cells, but I believe share nutrition among the non-feeding cells. A truly disjoint creature would need a metabolic system on both sides of the disjoint…

Workers in a given ant colony - really, daughters of the same mother in any hymenopteran species, all of which use haplodiploid sex determination - are more closely related than siblings in species with fully diploid sex-determination systems, but they're not clones.

Re: Insect Has Gears in Its Legs (2013)

#36

Post by [deleted] »

mindfulplay wrote: post #31

Truly fascinating. It makes me wonder how such a thing could be encoded inside a DNA. As in, is there a field of study similar to computer science/information theory on certain fundamental biological "laws of transformation"? Say, we have six billion or so pairs in the DNA. How could a series of transformations from those pairs with other proteins produce this complexity especially ones that requires a particular 3d…

[deleted]

Re: Insect Has Gears in Its Legs (2013)

#37

Post by nobodyandproud »

Klinky wrote: post #22
csomar wrote: post #18

Earlier quoted context omitted.

Actually it's the human bodies that are quite wasteful (so are humans themselves). Many big animals can keep going without food for months. And it's not just their oily fat reserves, they are much more efficient with energy.

The human body is good at being flexible and adapting to a wide variety of environments. You see it in a lot of areas of life, rigid efficiencies and flexible inefficiencies. Being more flexible has its costs and benefits. Humans are very much "jack of all trades, master of none".

No way.

Humans are long distance champions (ymmv).

As long as we can track an animal, we can run run them down to exhaustion.

Re: Insect Has Gears in Its Legs (2013)

#38

Post by wruza »

core-questions wrote: post #33
mindfulplay wrote: post #31

Truly fascinating. It makes me wonder how such a thing could be encoded inside a DNA. As in, is there a field of study similar to computer science/information theory on certain fundamental biological "laws of transformation"? Say, we have six billion or so pairs in the DNA. How could a series of transformations from those pairs with other proteins produce this complexity especially ones that requires a particular 3d…

I think we're still a generation or so away from getting to this level. Fundamentally, though, it doesn't seem to be too wild of a suggestion that DNA is going to end up looking like an incredibly complex, incredibly hacky computer program, utilizing every last potential possibility of its mechanical substrate. Think about demoscene or 80s video game programming, tight little assembly routines by developers that did…

This reminds me a first perceptron tutorial. An author described that to match a digit 9, ideally one layer matches a circle, another sees a lower curve and a result is then combined into output “neurons”. In reality, after you train a network, it has no circle-matching or curve-matching parts. Every part of it is just a random noise that you couldn’t reverse-engineer without pushing various data to that blackbox. We could’t even tell if matching F to 1 was a learning error or an intended behavior.

Re: Insect Has Gears in Its Legs (2013)

#39

Post by wruza »

nobodyandproud wrote: post #37
Klinky wrote: post #22

Earlier quoted context omitted.

The human body is good at being flexible and adapting to a wide variety of environments. You see it in a lot of areas of life, rigid efficiencies and flexible inefficiencies. Being more flexible has its costs and benefits. Humans are very much "jack of all trades, master of none".

No way. Humans are long distance champions (ymmv). As long as we can track an animal, we can run run them down to exhaustion.

Isn’t that because hairy animals often overheat quickly? (As opposed to being exhausted energy-wise.)

Re: Insect Has Gears in Its Legs (2013)

#40

Post by tcoff91 »

wruza wrote: post #39
nobodyandproud wrote: post #37

Earlier quoted context omitted.

No way. Humans are long distance champions (ymmv). As long as we can track an animal, we can run run them down to exhaustion.

Isn’t that because hairy animals often overheat quickly? (As opposed to being exhausted energy-wise.)

I’d imagine it’s also due to our bipedal locomotion, our ability to carry water, our intelligence helping to pick superior routes, and yes we have a cooling advantage compared to most other mammals. Maybe slow vs fast twitch muscle fiber amounts too?
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