Recent submissions

Comment · 2 months ago
That was kind of my initial point... there are far too many permutations that alter what you want to maximise to consider this as a good option right now. Environment, gene-environment interactions, epigenetics, polygenecity, pleiotropy, etc, etc.
Comment · 2 months ago
Great question! It maybe can be, but what is the maxima that is being solved for exactly? There are usually tradeoffs, the most common and prevalent is our body's immune response. If it's under-active, we might die from an infection. If it's over-active, we get diabetes, lupus, chron's, and (probably) lots of mental health disorders.

So, it's a bit context dependent, and definitely dependent on other mutations that have occurred in other parts of your DNA. Most complex diseases are "polygenic", meaning it's a culmination of quite a few factors that would contribute to a specific good or bad outcome.

So, yes, it could be modeled as a sort very context dependent with a lot of highly correlated non-independent covariates. We do use quite a lot of statistical and ML methods to understand the genome (I work in statistical genetics), but the complexity of biology has so far proved a tough nut to crack.

Comment · 2 months ago
I think people in HN (and in general) have to remember the central axes of evolution before digesting this kind of article. I've already seen comments like it's "odd that no species has ended up evolving a continuous maintenance system" and "sleep has a higher opportunity cost in humans" in this comments section.

This is a common, but poor framing of evolution. Remember: the only real rule with evolution is "did this evolutionary change mean they survived / reproduced more"? Evolution is not a local or global maxima solving function. I find this kind of attempt at interpreting selection common with engineers, programmers, etc.

Comment · 4 months ago
This is a pretty egregious misreading of both Hardin and Ostrom, where on earth did you get this from?

Hardin did not argue that private industry was more efficient. His paper described that with an unmanaged, private, unregulated open pasture that has no property rights, individuals will exploit it until it collapses. It wasn't used used as justification for privatization, if anything it was the opposite.

Ostrom did not argue that unmanaged resources don't collapse. Instead, she showed with data a third way of organising which was more involved with self-governing, communal rules to manage shared resources without resorting to either a private corporation or government control.

Comment · 1 year ago
I have to disagree with your take on "High critic score / low audience score". There is a swathe of more challenging, experimental, or art house movies that fall into this category. These reviews fill the void where another audience only place like imdb falls short.
Comment · 1 year ago
The old hacker news hug of death...
Comment · 1 year ago
Comment · 1 year ago
Comment · 1 year ago
Well no. It's not uncommon for p-values to be even lower than that. We are talking about a specific SNP (allele) having a specific mutation being predictive of a phenotype / outcome.

So, a specific SNP mutation being predictive of a gene expression / protein is basically a p-value of 0.

Can't speak for physics experiments, but this is almost certainly not a statistical error

Comment · 1 year ago
So, it is like that, but it's also not. A couple decades ago, with the advent of GWASes, because of all the multiple testing that was going on, there was an agreed new p-value threshold p < 5e-8. This was to account for multiple testing going on (how that number came to be requires more explanation of LD + other things).

That is the minimum threshold. This study found that peak was at p < 1e-37 or so. But that is where the biological analysis begins. Unlike social scientists, we don't stop with the statistical correlation, we then go on to look at what we know about that gene, the type of mutation, if it's a loss or gain of function, what role that gene has in various tissues, etc. And mendelian randomization is another way to unpick the causal direction of effect.

Not to say this is the truth or causal, but it's a lot closer to causal than what you are implying.

Comment · 1 year ago
I have never heard of FireDucks! I'm curious if anyone else here has used it. Polars is nice, but it's not totally compatible. It would be interesting how much faster it is for more complex calculations
Comment · 2 years ago

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