>BIoinformatics in the lab

>After yesterday’s talk by Dr. Bowdish (I just feel weird calling professors by the first name when referring to their talks), I walked away with several different trains of thought, one of which was the easy integration of bioinformatics into the research program she’d undertaken. The interesting thing isn’t so much that it was there, but the absolutely relaxed attitude with which it had been presented.

When I first started talking to professors about the interface between computers and biology or biochemistry, the field had barely even been given a name – and most of the professors were utterly confused about what computers could do to enhance their research programs. (Yes, I was an undergrad in the mid-90’s.) I remember several profs saying they couldn’t think of a reason to have computers in their labs at all. (Of course, at the time, there probably wasn’t much use for computers in the lab anyhow.)

There was one prof who was working on the edge of the two subjects: Dr. Patricia Schulte. Although she was working on the field of fish biology, somehow she was able to see the value and encourage her students to explore the interface of bioinformatics and lab integration – and she was the first person to introduce me to the term Bioinformatics (among many other topics: HMMs, Neural Nets, etc…)

Anyhow, at that point, I was hooked on bioinformatics, but finding the opportunity to do hands on work was nearly impossible. The biology professors didn’t know what it could do for them – and clearly didn’t have the vocabulary with which to express their interests in computational information. It was awkward, at times. One prof couldn’t figure out why I wanted to use word processors for biology.

To my great amazement, things have dramatically changed in the (nearly) decade and a half since I started my first undergrad, and yesterday’s talk was really a nice opportunity to contemplate that change. Dr. Bowdish’s talk included a significant amount of biology, genomics and bioinformatics predictions. When the predictions didn’t turn out (eg. the putative myristolation site wasn’t actually important), there was no accompanying comment about how unreliable bioinformatics is (which I used to see ALL the time in the early days of the field), and there was no hesitation to jump in to the next round of bioinformatics predictions (structure predictions for the enzyme).

I think even this quiet incorporation of bioinformatics into a young lab is incredibly encouraging. Perhaps it’s Dr. Bowdish’s past, having done her PhD in Dr. Hancock’s lab, who himself was an early adopter of bioinformatics predictions, or possibly it’s just researchers who have grown up with computers for most of their life finally getting into the ranks of academia. Either way, I’m impressed and encouraged. Bioinformatics gold age may not be here yet, but I think the idea that they’ll never become mainstream has finally started to fade from the halls of the ivory tower.

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