Are you positing that an enormous differential in genetic supply will result in no difference in reproductive strategy and therefore no difference in evolved psychology?
Or put another way, that everything we know about supply/demand curves and evolution is wrong?
I happen to be an evolutionary biologist and I said nothing about reproductive strategies. You would first need to establish a link between reproductive strategy and psychology (evolutionary psychology is a bit of a joke science, I'm afraid) and then between psychology and brain structure.
That's a link between the program and the hardware, which is the analogue of the demand that was set.
You can run the same program on different hardware, and run the same program on the same hardware and get different results. I'm not sure the analogy gets us very far.
Hopefully far enough to illustrate that "altering brain structure changes personality" isn't the same as "different personalities have to have a basis in brain structure."
I wasn't directly involved but the research group I'm part of did some earlier work mentioned in this paper (ref. 10) and I would be happy to answer any questions people may have.
This is really interesting stuff! One of the potential applications they call out is long-term data storage. How do you know that the stored data will actually last hundreds of years?
Also not part of this study, but an earlier one (ref 6). Basically DNA has been recovered from corpses that are thousands of years old. If stored properly, it is at least extrapolated to last up to millions of years [1].
You don't actually need to that much, as long as you can keep it dry and reasonably cool -- one idea we had kicking around was to use a cave of the sort that's used for long term seed storage (https://en.wikipedia.org/wiki/Svalbard_Global_Seed_Vault)
In principle a few hours but currently you have to outsource synthesis (i.e. writing) to a company and its an expensive process. Sequencing (reading) can be done more easily and has been dropping in price faster than Moore's law predicts.
hey there, i have two questions on your earlier work.
the assumed context is sending/reading a message via DNA is equivalent to de novo sequencing with 100% accuracy.
error-correcting via 4x overlap:
how many insertions, deletions, substitutions can it correct for? are some combinations harder to fix than others? for example, three insertions much worse than one deletion, or 5 substitutions, etc.
information storage / information blocks:
i'm guessing the 100bp segments have to do with the limits of hardware sequencing, but what limits the overall message size to 739Kb?
There are four copies of each part of the message so you can lose entire chunks and still be able to recover everything. As for subtitutions, unless you get the same error in 2 copies out of 4, there should be no problem.
The 739kb isn't a limit in any sense, the main limitation is that DNA synthesis is currently expensive.
related question, on putting messages into dynamic, living systems:
let's say the 'message' is so large it can only be inserted into a 'junk DNA' (non-conserved) region of the genome.
is it correct to assume there are less active/robust dna repair mechanisms to 'fix' the insertions, deletions, substitutions described above than in conserved regions?
what might some numbers be for errors rates in non conserved regions ( 2x, 10x,...) compared to conserved regions? or maybe one type of error is relatively much higher than another kind?
im guessing sources of insertion/deletion/substitution 'error' are mutations over lifetime of cell, and also replication errors in daughter cells.
> Modern classification schemes are so arbitrary and error-prone as to be essentially just a painful way to satisfy scientists' compulsion to shove things into neat little cubbies and has the negative side-effect of scaring students away from an otherwise fascinating subject.
What do you mean by "modern classification schemes"? If anything, molecular phylogenetics helped clarify earlier attempts at classification which used common morphological features.
R core developers are notoriously resistant to change. A number of glaring inefficiencies have gone unfixed for years, despite people submitting patches etc.
R core is generally motivated by ensuring that R continues to work as is, not by improving performance. You can argue whether or not this is a good idea, but in the absence of a comprehensive unit test suite, it's pretty hard to improve performance without breaking behaviour.
It's difficult to see how this rationale can possibly justify ignoring a 10x speed up in vector-matrix multiplies (and similar speedups for some other matrix multiplies) that can be achieved with a modification affecting a dozen or so lines of easily-checked code.
I'd expect it's less brave for someone from an industry and social circles comfortable with implants, injections scalpels, etc, and with a bit more than a "livelihood" to ease the experience. The experience would surely be more foreign to the average woman, requiring more bravery. Angelina isn't dependent on the look of her breasts for her "livelihood". 87% risk is a no brainer.
Her going public about this has got a great potential to raise awareness and make other women more likely to consider this course of action. The sad reality is, however, most women won't be able to afford the reconstructive surgery (or to have it done to the standard Angelina Jolie has).
I think more importantly it brings up the very real human implications of the debate against patenting human genes, which has most recently been centered around the BRCA gene.
