Today I read an article at the “Daily Beast” by Megan McArdle that really struck a nerve, entitled “The Absurd Lies of College Admissions”. It begins…

A high school student has penned an open letter to the colleges that rejected her, published in the Wall Street Journal.

“I also probably should have started a fake charity. Providing veterinary services for homeless people’s pets. Collecting donations for the underprivileged chimpanzees of the Congo. Raising awareness for Chapped-Lips-in-the-Winter Syndrome. Fun-runs, dance-a-thons, bake sales—as long as you’re using someone else’s misfortunes to try to propel yourself into the Ivy League, you’re golden.”

I highly recommend that you read the whole thing.

I don’t agree with everything this high school student wrote – for instance, the type of thing she describes is more characteristic of some Ivies than others – but there is a lot of this at certain Ivies and one in particular that I won’t name.

For that matter, I don’t agree with everything Megan McArdle added. But I think there is an important thing for any high school student to consider: What do you want to get out of college, and do I need a degree from an “elite” school to get it? For instance, do you want to own a home? Get married? Raise kids and be able to pay for their weddings or college degrees should they be interested in going? Do you want to create things? Will people pay for the things that you create?

And will the label on your diploma affect any of these greater goals? Because after four years, nobody cares where you got your degree. An engineer with a B.S. from Princeton or Cornell will work side by side with engineers from UT Austin, Penn State, Rutgers, RPI and Georgia Tech, make the same amount of money and have the same career track.

If you don’t have those greater goals that allow you to calculate a “return on investment” for your college – and more importantly, major of choice – you may have bigger long term problems than concocting fantastic stories about extracurricular activities. Keep your eyes on the prize!

Deterministic versus stochastic modelling in biochemistry and systems biology will be available on March 28, 2013. If you plan to offer a course on bioinformatics, computational biology, or systems biology in the fall semester or quarter of 2013, you’ll have plenty of time to review the text and get an order in to your campus bookstore.

The book is well structured for a single-semester course, with about a week devoted to the material in each chapter. If you have questions about the contents of the book and want to know how you can use it with your existing course plan, please don’t hesitate to contact me.

I’m pleased to announce that my book with Paola Lecca and Ferenc Jordan (of the Center for Computational and Systems Biology (COSBi)) is now available for pre-order!

Paola, Ferenc and I wrote Deterministic Versus Stochastic Modelling in Biochemistry and Systems Biology to target advanced undergraduate students and graduate students. The book bridges biology, physical chemistry and computer science – filling the gaps that may be experienced by students of classical disciplines as they enter the exciting interdisciplinary field of systems biology. The book includes “hands on” examples including Matlab examples for students with limited programming or simulation experience.

A few weeks old, but the facts don’t change much in that time: Why does U.S. fail in science education? (from the Pittsburgh Post Gazette). I highly recommend that you read the whole thing. Here’s the highlight:

One of the things that strikes me about these responses is that they may be attributed to marketing: astrology is obvious, but the belief that antibiotics target viruses is, to my impression, a result of marketing approaches taken for household cleaners. Then, it may be a consequence of a lack of knowledge: perhaps many people don’t realize that viruses, fungi and bacteria are completely distinct forms of life?

Let’s assume my hypothesis is correct: perhaps it works both ways? Consider the sound vs light question. About 14% thought sound moves faster than light. Why such a small fraction? I’d guess that it’s because just about every sci-fi show has spaceships that travel “faster than light”. Who even thinks about the speed of sound anymore? As I watched “The Right Stuff” recently on Netflix, I couldn’t help but think “Oh, how quaint” as the test pilots were romanticizing the sound barrier.

The article proposes that the so-called “science gap” results in part from motivational differences, patience in learning, etc. That may be true. But it seems to me that people are likely to believe in astrology, etc. regardless of their motivation or scientific training if they’re accepting the marketing.

So there are really two issues: erroneous beliefs due to marketing of one variety or another, and science education, with an undefined overlap. If you want better numbers in the chart above, you need better science marketing, not just better teachers or students.

Fascinating and timely story about the Chernobyl disaster, 25 years ago today: Japan can learn from Chernobyl nuclear reactor disaster

Franciscan University of Steubenville physics professor Alexander Sich did extensive research at the site of the Chernobyl nuclear reactor disaster.
Alexander Sich’s long-standing goal has been to dispel myths surrounding the 1986 Chernobyl nuclear power plant accident.

Japan’s Fukushima Daiichi nuclear power plant accident in March revived many of those myths, including claims the Soviet Union ended the Chernobyl meltdown in Ukraine by burying exposed nuclear fuel under concrete and other materials.

Mr. Sich knows firsthand that didn’t happen.

Read the whole thing!

I love creative graphical representations of data and am a bit of Tufte disciple, I have to admit. If you are too, and you use Linkedin, try this out: http://inmaps.linkedinlabs.com/.

(Click for the full image)

Fascinating story from Discover Magazine

As of 2007, humans had the capacity to store 295 exabytes. An exabyte is 1018 bytes. If you think of the gigabytes (a billion bytes) in which your hard drive space might be measured, an exabyte is a billion of those gigabytes. Another size comparison: Astronomers, by necessity, are designing new information processing techniques to help them grapple with the coming age of “petascale” astronomy, because they’re starting to get more information than they can handle. “Exa” is the prefix after “peta”; it’s a thousand times more.

How long until people speak of “moles” of memory? Avogadrobytes?

Obviously from xkcd. I think I sing all of these to my daughter, including the Katamari Damacy theme. Right now, she can say “ma ma”, “da da”, “ba ba” but not “na na”. When that happens, home will be very musical!

This article from PLOS Medicine is a must-read for any biological scientist and a nice follow-up to my post from yesterday. The title (which I’ve used as the title of this post) says it all, but the abstract says it better

There is increasing concern that most current published research findings are false. The probability that a research claim is true may depend on study power and bias, the number of other studies on the same question, and, importantly, the ratio of true to no relationships among the relationships probed in each scientific field. In this framework, a research finding is less likely to be true when the studies conducted in a field are smaller; when effect sizes are smaller; when there is a greater number and lesser preselection of tested relationships; where there is greater flexibility in designs, definitions, outcomes, and analytical modes; when there is greater financial and other interest and prejudice; and when more teams are involved in a scientific field in chase of statistical significance. Simulations show that for most study designs and settings, it is more likely for a research claim to be false than true. Moreover, for many current scientific fields, claimed research findings may often be simply accurate measures of the prevailing bias. In this essay, I discuss the implications of these problems for the conduct and interpretation of research.

Read the whole thing for a fascinating read that doesn’t require a Ph.D. to follow.

What I find truly fascinating is that there’s no specific scope restriction to “biological” or “medical” research per se. Bad science happens in the physical sciences too, and for the same reasons: Human bias. As long as the data pass through human eyes and human minds with human biases, they can be filtered or disposed of as “bad data” instead of refutations of prevailing dogmas or novel discoveries.

A favorite Asimovism of mine is “The most exciting phrase to hear in science, the one that heralds new discoveries, is not “Eureka” but “That’s funny…”” But if you immediately reject “That’s funny” because of your prejudices, where is the science? Quoth Frank Zappa: Who are the brain police?

This article from the New Yorker is quite possibly the best science article I’ve ever read. A snippet:

But now all sorts of well-established, multiply confirmed findings have started to look increasingly uncertain. It’s as if our facts were losing their truth: claims that have been enshrined in textbooks are suddenly unprovable. This phenomenon doesn’t yet have an official name, but it’s occurring across a wide range of fields, from psychology to ecology. In the field of medicine, the phenomenon seems extremely widespread, affecting not only antipsychotics but also therapies ranging from cardiac stents to Vitamin E and antidepressants: Davis has a forthcoming analysis demonstrating that the efficacy of antidepressants has gone down as much as threefold in recent decades.

For many scientists, the effect is especially troubling because of what it exposes about the scientific process. If replication is what separates the rigor of science from the squishiness of pseudoscience, where do we put all these rigorously validated findings that can no longer be proved? Which results should we believe? Francis Bacon, the early-modern philosopher and pioneer of the scientific method, once declared that experiments were essential, because they allowed us to “put nature to the question.” But it appears that nature often gives us different answers.

Read the whole thing: http://www.newyorker.com/reporting/2010/12/13/101213fa_fact_lehrer?currentPage=all