Isabelle: About a month ago, I joined the Barrett-group at the Sanger institute. Coming from a molecular biology background and ending up in a team of computational biologists, statistical geneticists and bio-informaticians, it soon became clear that I was going to have to learn a whole new vocabulary: the ‘others’ love terms ending in *ash: bash, hash, slash (forward and backward!), dash…; and their day to day language includes things like grep (‘grepped’), awk, sed, syntax, R, perl, python, unix, linux (what is actually the difference between all these things??), … . Although I thought I was getting along very well before, manipulating datafiles in MS Excel and here and there using some command line programs (already making me feel like a computer wizard), it here turned out quickly that I was far from being a computer genius. I got lucky though, since one of my new colleagues appeared to be a ‘partner in crime’, also having a background in molecular biology, but having been introduced into the wonderful world of scripting and programming already years ago.

Iris: although I made the switch a while ago, until I started at Sanger I have always worked in a clinical setting so the wet lab was always just around the corner. In the Sanger introduction day there is a lot of attention placed on the campus desire to be as green as possible. So when on my first day was mentioned that I should get access to the farm so I can work on it, for a second I considered whether or not this actually meant I would have to do some farming! As I managed to even let a cactus die this was a bit scary to me. Luckily when they mentioned all the programs installed on the farm I realised the farm was the name of their computer cluster!!

Isabelle and Iris: Despite all the differences, we are convinced that the molecular/computational biologist partnership represents a golden (academic) combination. Wasn’t it Bill Gates who called biology a “sister science” to computer science: “I think a lot of the breakthroughs will be made by people who were trained in biology and computer science”. Although one can discuss about how far a biologist needs to go in learning computer science and vice versa, it is certainly true that the interdisciplinary approach (either within one person, or by close collaborations between differently-trained persons) will open doors to great achievements. While the statistical geneticist gets excited about a highly significant p-value, we can’t help but thinking: ‘very nice, but what does it do?’… It is this combination of different ways of thinking, and the different questions we ask, that will make science move forward. But then we first need to try to understand each other. In follow up posts we will come up with some SOPs for working in a lab as opposed to an IT setting, and a (hyper)dictionary including specific terms from the lab-world and their counterpart in IT-land. We would like to encourage everyone to comment on this post, and to share their personal experiences of entering an IT-zone being trained as a molecular biologist. And also of the reversed: what do IT people really think of lab-people, and how did they feel when they were thrown in the lion’s den?? As an exercise, we are committed to reverse roles for our team, and to introduce our team members into the wonderful world of the lab with a basic lab practicum day/week. An extensive report (with pictures) of this will be posted – stay tuned!

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  1. Great to hear two more biologists are taking steps to gain skills in computing, we definitely need more of this to help biology progress in the 21st century!

    Recently I put together a “Top N” list of reasons do do a PhD or Post-doc in Bioinformatics/Computational Biology, which might be of interest to you/your readers:

    This post also generated some discussion on the web which is also worth checking out for more perspective on these issues:


    I’ve also subsequently discovered a really nice list of “10 Steps to Success in Bioinformatics” by Webb Miller, that is also definitely worth reading:

    Best of luck, Casey

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  3. I totally agree that a combination of computer science and biology is necessary for future progress in science. The amount of genetic data generated due to the advances in technology is huge. Well! I know someone who sometimes prefers to manually count, for instance, the number of females in a sample of 1500 people! But I can’t imagine that handling such huge genetic data would be possible without computer science.