Depression: A genetic Faustian bargain with infection? [Emily Deans/Evolutionary Psychiatry]. Discusses the Pathogen Host Defense (PATHOS-D) theory of depression described by Raison and Miller [pdf]. Genes that make people susceptible to depression may also protect them from infection. Depression is associated with brain inflammation; inflammation is also part of the immune response that combats infectious disease. “Since infections in the developing world tend to preferentially kill young children, there is strong selection pressure for genes that will save you when you are young, even if those genes have a cost later in life.”
The people of the petabyte [Venkatesh Rao/Forbes blogs]. An “informal taxonomy and anthropological survey of data-land” based on Rao’s observations at the Strata conference. Apparently everyone’s a data scientist now:
The taxonomy part is simple. Apparently the list of species in data land is very short. It has only one item:
What is the value of big data research vs. good samples [from LinkedIn Advanced Business Analytics, Data Mining and Predictive Modeling group]. Interesting and lengthy discussion from LinkedIn’s Advanced Business Analytics, Data Mining, and Predictive Modeling group on whether/when sampling vs. big data sets should be used.
The real-world experiment: New application development paradigm in the age of big data [James Kobielus/Forrester].
This year and beyond, we will see enterprises place greater emphasis on real-world experiments as a fundamental best practice to be cultivated and enforced within their data science centers of excellence. In a next best action program, real-world experiments involve iterative changes to the analytics, rules, orchestrations, and other process and decision logic embedded in operational applications. You should monitor the performance of these iterations to gauge which collections of business logic deliver the intended outcomes, such as improved customer retention or reduced fulfillment time on high-priority orders.
Nutrition advice: The vitamin D-lemma [Amy Maxmen/Nature]. “The difficulty of distilling strong advice from weak evidence.” This is a key challenge for researchers/statisticians/data scientists in any domain, not just in health.
Will Amazon offer analytics as a service? [Quentin Hardy/Bits]. Interesting to get an idea what that might look like. I don’t think, though, this would compete with SAS and similar software as the post implies. Would someone looking to implement a product recommendation engine implement it in SAS? Probably not. For example, Google is said to use R for model exploration and prototyping, then puts them into production using Python or C++. I feel a “choosing your analytics tool” post coming on.
Community college budget cuts drive students to for-profit school [Chris Kirkham/Huffington Post]. Balanced coverage of why students turn to for-profit schools and the pros and cons of such choices. My observation: community college tuition is artificially low due to government subsidization while for-profit tuition is artificially high, again because of government interference (in the form of financial aid). No market forces to bring about a reasonable balance between supply and demand. The big losers are students (and taxpayers).
Benchprep is codecademy for any subject, high school to med school [Josh Constine/TechCrunch]. “Eventually, publishers might get a clue that interactive digital education is going to destroy their paper book business. If they’re smart they’ll start developing their own courses or raise licensing fees. Until then though, BenchPrep will be the savior of anyone frustrated by the static book-learning experience.” I’m pretty certain some big textbook publishers see that already.
Forget dieting, try intermittent fasting [Josh Ozersky/Time Ideas]. “And that’s why instead of eating healthier, I’m going for longer stretches without eating so I can actually enjoy a whole meal. I don’t starve myself; I drink a protein shake if I get hungry and consume endless glasses of diet iced tea. People tell me this is bad, that I will soon gain back all the weight I’ve lost – and these rejoinders are always given with a smug malice, as if the people uttering them actually despise me for trying to compensate for the pleasures of the plate.”
I fast most days at work until about 2 or 3 pm, then have a small snack. I eat whatever I want once I get home from work around 5 pm. I find this allows me to eat generally what I want while maintaining my weight at a level I’m happy with. I have found, like Josh, that people get really upset about this plan, almost offended that I would eat this way. Funny how everyone thinks they know what is healthy and what is not, despite the difficulties in determining that (see first link in this post).