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It's written in Perl.
Perl is (amazingly) still a thing in 2021 in quantitative biology, at least in big national labs I'm familiar with. See e.g. https://www.amazon.com/Mastering-Perl-Bioinformatics-James-T...
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Don't sell yourself short. Your ability to grok the summary (or abstract) of a research paper is probably not much worse--and possibly better--than a typical journalist, even a journalist at the NYT. Especially relative to younger journalists, who seem to rely on Twitter and other social media to contextualize things.
I am generally surprised by the inability of journalists to grok research papers, but I think the age thing goes the other direction than what you suggest. General scientific/numeric literacy among people who don't work in science seems higher in the younger generation than the older to me.
With some scientific literacy, you may be able to understand the central claims made in a paper. Or you may misunderstand them, because you may not be aware of the specific meanings of some words that are also used in everyday language. You may not be familiar with the context the paper was written in or with the best practices in the field. Hence you may not see the implicit assumptions that were made or know the justifications for certain choices. Because you are not an expert in the topic, you may not see the immediate consequences of the claims and are likely to take them too literally.
It doesn't help that the authors probably didn't understand the results fully either. Most papers are difficult to understand, because they discuss early insights rather than final results. Clarity often comes with a better understanding years after the initial publication.
“It should make us worry,” said David Enard, an evolutionary biologist at the University of Arizona who led the study, which was published on Thursday in the journal Current Biology. “What is going on right now might be going on for generations and generations.” Should it though? Seems like we've survived this many times as a species, and now have the technology to combat it! I'm more optimistic with this information…
> Should it though? Seems like we've survived Someone survived - but for the mutations to have a selection benefit strong enough to dominate that gene pool there would have to be more people who didn’t survive than did.
To be pedantic: the gene pool is mostly influenced by anything that prevents reproduction, i.e. if you have your kids, and then die that doesn't affect the gene pool to a first approximation (there are selection pressures of becoming an orphan, but they are likely usually very weak. If being an orphan makes it more likely one will have kids or more likely to have more kids than one would have otherwise, then the selection pressure will select for death, which is inverted from what is naively thought! Edit: And if you are older and have never had kids and die, there is very little chance for selection pressure.).
People keep posting archive links to "non-paywalled" copies, but the study itself has freely available full-text not behind a paywall. No need to read the NY Times at all. Just go straight to the source: https://www.cell.com/current-biology/fulltext/S0960-9822(21)...
Here is the source code, AFAICT: https://github.com/DavidPierreEnard/Gene_Set_Enrichment_Pipe... I've been involved in GWAS before, so have an inkling of what's going on. I love the creativity in this paper. The stuff is super fascinating, but the pipelines are still very primitive—so I encourage programmers to get involved in bioinformatics if you like this stuff! In the future I expect we see work like this accompa…
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Perl is (amazingly) still a thing in 2021 in quantitative biology, at least in big national labs I'm familiar with. See e.g. https://www.amazon.com/Mastering-Perl-Bioinformatics-James-T...
It’s hard to beat Perl when it comes to string matching performance and flexibility.
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It’s hard to beat Perl when it comes to string matching performance and flexibility.
Actually, no. But it's some sort of technical heritage/baggage.
The language itself is definitely better suited to writing those regexes all over the place, so if you have two axes of performance & regex usability, I wouldn't discount Perl for those use-cases. I do suspect though that the bioinformatics field overindexes its use of Perl because that's what they know even though it's less well-suited for other things. That being said, that's usually why programmers might choose Python. Something to be said for familiarity & access to a thriving software ecosystem you're familiar with.
So - how did this virus spread through the population? 20 kyrs ago people didn't live in cities but in small bands of a few dozen people. It's easy to see how an epidemic might spread through a village but how would it move between isolated groups?
And how did they ever survive, without masks, lockdowns and vaccines?
Like no-one at all is claiming that if we don’t use vaccines or take precautions against covid, humanity will be wiped out.
Is it a best practice nowadays to use word "coronavirus" for all the viruses with the particular molecular structure pattern instead of word "flu"?
I'd love to never hear about another coronavirus again. We went too far prescribing a certain agenda in the last year, and it's time to reflect on that. In my opinion studies and articles like this are doing more to fuel the fear porn than they are at teaching anything substantial.
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And specifically about a pandemic, even if 50% of humans died in it the species would continue, but that would very much be something to worry about. Even at much lower percentages it would be worrying. Or the fact that it could continue for generations.
Fact it could continue? Or opinion it could continue? There's a significant difference. The latter is not science.