Books, Science

Life out of sequence – Hallam Stevens’ data-driven history of bioinformatics


How do people like you ever get last-author papers?” The person who asked me this question in 2008 during the interview for my current job was (and still is) a well-known stem cell biologist with decades of experience in science. But she still didn’t really know what to think of ‘people like me‘: bioinformaticians and computational biologists. Aren’t bioinformaticians just service providers? Handy to have, but without any real scientific vision and contribution? She clearly worried about my ability to do independent research.

And she wasn’t alone. A couple of years later I interviewed for an EMBO fellowship, which I didn’t get because the panel –mostly cell biologists, no one computational or from genomics or medicine– thought my group was a “mathematical service unit” and my research was “overly driven by my collaborators”. I’m still not sure what a ‘mathematical service unit’ could be (proofing theorems on demand maybe?) but their comments showed me how far removed their research practice was from my own.

Even though bioinformatics is by now an established field these personal experiences show that ‘old school’ biologists, who form the scientific establishment and direct mainstream research, are still very uncomfortable with ‘people like me’ who were trained in other disciplines, pursue biological questions different from their own, and use approaches not covered in classical biological training.

Life Out Of Sequence Cover

Hallam Steven’s book Life Out Of Sequence, A Data-Driven History of Bioinformatics starts with the tension between old and new biology that ‘people like me’ experience every day and describes the way biology has been and is being changed by computational methods.

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The hedgehog and the Quants


Nate Silver bashing everywhere I look. For example in the New York Times. Paul Krugman does it. And someone called Timothy Egan. `Creativity vs. Quants‘ is the title of his OpEd – how silly! Does he really thing we quantitative folks are mechanical calculation machines devoid of any creative thought? If you think quantitative work is not creative, you just haven’t done it yet.

Intimidation by quantification

Much more interesting, I thought, was Leon Wieseltier’s take in the the New Republic. I really like Wieseltier’s phrase ‘intimidation by quantification’ – this is how my biological collaboration partners must feel when I bombard them with p-values.

Wieseltier discusses the old idea of the hedgehog and the fox (dating back to ancient Greece) that Silver had used to explain the Fox logo of FiveThirtyEight: “The fox knows many things, but the hedgehog knows one big thing.”

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Duty Calls, Science

Don’t believe the petabytes! Against Big Data Empiricism

The data never speak for themselves; and even Big Data doesn’t change that.

“The business of Big Data, which involves collecting large amounts of data and then searching it for patterns and new revelations, is the result of cheap storage, abundant sensors and new software. It has become a multibillion-dollar industry in less than a decade,”

writes Quentin Hardy at Big Data is everywhere, even in medicine. Just have a look at Atul Butte‘s presentation at TEDMED2012:

“Who needs the scientific method? Vast stores of available data and outsourced research are simply waiting for the right questions,” claims Atul Butte.

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The one and only scientific method

In martial arts dojos practitioners often revel in guidelines, rules or proverbs that some ancient or not-so-ancient master has coined. When I spent time in a JKA karate dojo we would recite the dojokun after every session: Seek perfection of character! Be Faithful! Endeavor! Respect others! Refrain from violent behaviour!

In science –where everybody strives for novelty– the inclination to repeat ancient lore is less pronounced. And so I was surprised to find the lab rules of the Noyes lab in the Lewis-Sigler Institute at Princeton.

Some of their rules are a bit clichéd, like “Dream big” or “2 is more than 1“, and some are too specific for my own research, like “Always run a ‘no insert’ ligation control“. Also, the whole thing is a bit tongue-in-cheek, I’d guess.

But the very first rule they list got me all excited, because it is the closest thing I have ever seen to a unifying principle underlying all of science:

If it sounds like more work, it’s probably the right thing to do.

From now on, after each and every groupmeeting, I will make everybody in the lab recite this gem of scientific wisdom.