Why desperate?

You may be wondering about the title of this blog.

Early in my bioinformatics career, I gave a talk to my department. It was fairly basic stuff – how to identify genes in a genome sequence, standalone BLAST, annotation, data munging with Perl and so on. Come question time, a member of the audience raised her hand and said:

“It strikes me that what you’re doing is rather desperate. Wouldn’t you be better off doing some experiments?”

It was one of the few times in my life when my jaw literally dropped and swung uselessly on its hinges. Ultimately though, her question did make a great blog title.

12 thoughts on “Why desperate?

  1. Believe me, you’re not the only one who has faced this. I sometimes have a very hard time convincing my PI
    about the power of computational biology (he’s a die-hard old school biochemist). He’s gradualy turning around,
    but it’s been a lot of work!

  2. Yeah — shortly after I started grad school back in 1992 (in those days, “bioinformatics” hadn’t been coined,
    or at least I hadn’t heard of the term if it had), I was informed that my advisor (and by extension, me) was
    a “bottom feeder” because all he did “was write programs and analyze other people’s data”.

    Somewhat ironically, given that writing programs and analyzing data of others is now more respectable,
    my former advisor is now mostly doing wet-lab stuff.

  3. I find that the most successful labs have either (1) an in-lab integration of wet-lab and in silico analyses,
    or (2) a collaboration with outside labs to complement in-lab work. Even NIH funding in the states seems
    to be moving towards this approach.

    Purely computational research (with a few exceptions) are becoming harder to fund unless one finds a way
    to test out analyses with wet-bench research. The flip side of that is wet-bench researchers (like me) are
    finding that you must be computationally savvy in order to survive in highly competitive fields. A double-edged sword.

  4. Neil mate,

    I feel your pain. I heard this too, during grad school recruitment. I should have run for it too.
    Instead I mistook the nobility of the struggle as something worthwhile.

    This is by far the funniest thing I’ve heard in a long time.

  5. Yes, working with biologists is difficult. There is a reason for computer science people trying to stick together. It’s definitely more fun in the short run to work with people that understand what you’re doing.

  6. Now this may surprise you. I´m on the opposite situation: a graduate biologist slowly turning into a computational biologist (I wouldn´t say “computational scientist”, I´m far from it). I´ve spent my whole graduation doing wet lab, and heard of bioinformatics only upon entering Master´s Degree. Now, I´m finishing my Master´s only in bioinformatics, and with very nice results! Didn´t do any wet lab experiments in my Masters. Tell you what, computational biology is not only fun, but also essential to experimental biology, but like you said, even I, a former wet lab biologist, have heard the “rather desperate” discourse. Wet Lab fanboys usually are stuck to their paradigms. Funny thing is, sooner or later even fanboys come asking for help to the ‘bottom feeders’ of biology.
    Some people just can´t get that Luddites idea off their heads: “Never praise a machine, lest it take away your job”.
    Just to make things clear: I still love wet lab Biology and could anytime drop Bioinformatics and retake the workbench. The difference between me and my fanboy colleagues is that I realized the obvious: computational biology nowadays is a need in biology, they must walk together.

  7. The funniest is when you have a biologist trying to teach a statistician the correct statistics to apply to their data..!

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  10. My biostats boyfriend came across this post recently and it amused him enough to forward it on to me. I can’t really relate to it, but thank you for making him feel like less of a weirdo.

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