alsocasey

Personally, Bash on Ubuntu on Windows is a fine solution for my most common use cases.

I think the most egregious example is latter seasons of The Big Bang Theory clocking in at 16 minutes. That's ~50% ads.

In the case of vaccines specifically, there is just a surprising amount of things we still don't understand.

Vaccination is positively ancient technology (Smallpox circa 1796), but it is still difficult to say why e.g., some vaccines are broadly effective at producing immunity and some aren't (and what the factors at play are in the recipients), or why we can produce successful vaccines to some diseases and not others.

A specific example: the efficacy of BCG vaccination (tuberculosis) varies by manufacturer and the reasons for why that is are still unclear.

There are a number of large NIH-funded initiatives that aim at understanding the complex cellular and molecular interactions that result in immunity as a result of vaccination under the Human Immunology Project Consortium (a bunch of high profile papers in Cell, etc. over the past few years).

There is so much money circulating in private markets, but employees just can't access it. This seems pretty unfair to me.

Isn't this almost certainly by design?

I haven't looked into their new minion much yet, but how cheap are really talking about?

Originated in the 'magrittr' package. The early tidyverse used a different pipe before depending on magrittr's version.

Not to mention 'tweaking' required.

I bought directly and was passed around by Google and Huawei support for months (and multiple calls; hours of my time wasted - why can't anyone just do support by email anymore?) before ultimately giving up on getting the constant battery issues addressed. Initial contact was precisely 3 weeks outside of the warranty period for the now well-documented phone shuts off when battery reaches [15|30|50]%.

I feel like I purchased a year's worth of problem-free phone experience for nearly $CAD900. To me, that's not great value.

Is this "grammar of graphics" any good if you invest more time in it?

For some, it was probably one of THE things that kept them using R over something else. Yes, definitely worth it.

Overemphasis on commercialization is a common complaint of the current funding situation in medical research, so I don't think we're failing for lack of interest in commercial exits. In fact, many scientist are serial entrepreneurs.

Moreover, many discoveries that went on to make a lot of people a lot of money had no obvious commercial application when they were first being researched... Predicting future markets is hard.

Quant-itative analyst. Yes, industry jargon.

Turning to the Vulkan API allowed me to comfortably play at 1440P, Ultra, 60FPS on my (aging) 280X... That just blows my mind.

I think this is true, but it's also the case that businesses that cater to the very rich are doing very well. My wife works for a luxury retailer who's Vancouver location is seemingly supporting the entire company with it's sales. Revenue has basically tripled over the past 4-5 years.

Any chance you might be able to expand on this? I don't dislike OneDrive, but I've started to run into more and more issues with various machines falling out of sync unless I restart the OneDrive service to force changes to be detected... Dropbox has the same issue on those machines, so I'm not really sure what 'causes it.

Many (most) of the things we're interested in measuring in blood are bound to some sort large macro-molecular assembly... be it cells, lipid vesicles, large protein agglomerates, etc.

Faster because it isn't (currently) using compression (which rds uses by default) or faster period?

Either way, the idea of mixed Python/R pipelines with feather file intermediates input/outputs is pretty sweet. Learn in scikit, save to feather, plot in ggplot2... using Make to tie the pieces together?

Large scale genomics initiatives certainly can be 'Big Data', but with the costs of read generation continuing to decrease, the pipelines described in the paper are going to come into the hands of smaller groups and be applied to smaller studies... the RNA-Seq pipeline described in the paper is anything but big - an experiment with 20x the number of samples can be run on commodity hardware overnight - but it is the type of study a small lab might want to run. And for that type of setup, there's really no need for a large infrastructure setup.

There will be (are in fact) one-click, cloud-hosted solutions for analysis, but given how quickly tools have evolved in this space, there will always be groups wanting to run on their own hardware so as to experiment with the latest new developments.

It should manage drawing in OneNote ok, though.

This is very much appreciated:

1. As mentioned by others, there really is very little data on HD failure rates.

2. When you first published your blog on failure rates across HD brands/models and SMART attributes many, myself included, suggested it might be more illuminating as a predictive modelling exercise. This data allows others to do that now, which is great!

Does anyone happen to know whether the quad-core atom mentioned would be sufficiently powerful to handle being a Plex client or Steam streaming client machine? This would make a remarkably cheap living room client PC.

I'm in biomedical sciences, have a Ph.D. and will be a professor at a very good school soon, but I don't give a crap about somebody's degrees.

Many funding opportunities in academia are still tied to holding a graduate degree though.

It is until you realize how complex it is to quantify the costs to be balanced (early detection treatment costs, quality-adjusted life years saved, radiation exposure risks, etc.)

The only odd thing about this answer is that farmer 1 apparently decided to lower prices after selling 9 of his 10 chickens in the morning...

And Windows 8, Chrome.

The R portion needs some serious filling - for starters: you include the Julia wrapper to glmnet, which was originally implemented in R.

glmnet - lasso/ridge/elastic net glm models.

e1071 - SVM classifiers.

randomForest - random forest classifiers.

mixOmics - a good collection of component-based approaches (PCA, ICA, PLS, etc. includes sparse variants of all of the above is feature selection is required).

caret - similar to Java's Weka.

The real problem in the field is that diagnosis is often a relatively poor gold standard to learn against in many more complex (or poorly understood) diseases.

Looking at my own graduating class... it's not lack of talent, it's lack of opportunity. Many (most) graduates end up taking jobs south of the border within their first year post-graduation.

Diamonds are hard in that they resist scratches very well, but can shatter rather easily from impact (not very tough).

2) What actually causes "disease"? This implies to me that germs per se are not really the explanation.

IBS (and Crohn's, which is really just a type of IBD), is an immune disorder characterized by chronic, uncontrolled inflammation. All the disease's symptoms stem from this state, so the specific germs involved may or may not be all that important, the body's reaction to them is. When you get down to it, many disease states are just a consequence of regulation of inflammation failing at a critical location.

It seems a natural consequence of the popular continual-development, release-early-release-often model of software development.