This post is part of a series that interviews some notable bioinformaticians to get their views on various aspects of bioinformatics research. Hopefully these answers will prove useful to others in the field, especially to those who are just starting their bioinformatics careers.

Karin Lagesen is a bioinformatician working at the Department of Medical Genetics at Oslo University Hospital (OUH), where her work focuses on developing platforms for personalized medicine through the use of high-performance computing.

She is also an Associate Professor at the University of Oslo's Department of Informatics, where she is listed as being in the Biomedical Informatics (BMI) research group as well as a participant in the Computational Life Science initiative (CLSi). She also holds a part-time position at the Norwegian Veterinary Institute (NVI).

So to recap: Karin currently works at the NVI as well as the BMI and CLSi of the DoI at the UiO, and also the DMG at the OUH. I'm kind of amazed that she knows where to turn up for work each day!

During her PhD Karin helped create the program RNAmmer to provide consistent and rapid annotation of ribosomal RNA genes and as a post-doc she helped decipher the cod genome. Oh and did I mention that she also works on the Software Carpentry project?

You can find out more about Karin by reading her 'The Devil in the Details' blog, or by following her on twitter (@karinlag). And now, on to the 101 questions...

001. What's something that you enjoy about current bioinformatics research?

I am really enjoying the diversity of people that I get to meet. Bioinformatics is a field that draws from a lot of different knowledge pools — everything from mathematics, to algorithms, statistics, evolutionary biology, molecular biology, cell biology, microbiology and more is useful in bioinformatics. The consequence is that I have had occasion to meet and collaborate with a lot of interesting people and had the opportunity to learn a lot of new and interesting stuff. As a self-proclaimed knowledge junkie that is probably one of the biggest perks that come with working within the field.

Another exciting thing is the influx of “traditional” wet-lab biologists into the field. As a Software Carpentry instructor, I have had the opportunity to teach people basic computational analysis skills, including basic programming. It is a lot of fun seeing people being suddenly able to answer pretty complex questions after learning things that for me have become relatively easy, but which I know can be really big stumbling blocks for somebody new to it. A corollary to that is that I have a lot of fun seeing all of the weird and wonderful research questions that people come up with.

010. What's something that you *don't* enjoy about current bioinformatics research?

This one is a bit difficult, because there is little in bioinformatics research per se that I dislike. I love seeing all of the new development going on, so that part is fine. The one thing that keeps getting to me is the hurdle race that having a scientific career has become. I see people with interesting and good ideas leave research, simply because they are too exhausted to play the game anymore. I believe we are losing out on a lot of potential good research due to the way things are structured today.

011. If you could go back in time and visit yourself as an 18 year old, what single piece of advice would you give yourself to help your future bioinformatics career?

I would tell myself to tinker a whole lot more. The best way of learning this is to do stuff. Many of the things I do now have been greatly helped by working on side projects — my own or others’ — that might not have been what I should have been doing at the time. I have been greatly helped by incidental knowledge I picked up on Google, on newsgroups and forums, and by talking to people. Never underestimate the usefulness of things randomly picked up in conversation.

I would also tell myself to get involved in an open software project, a project with multiple collaborators all over the world. The skills that can only be learned by coding in collaboration are something that I am only learning now.

100. What's your all-time favorite piece of bioinformatics software, and why?

I think I have to go a bit old school here and simply say the Unix command-line. That is the one thing that makes all of the rest possible. The command-line itself is incredibly flexible, and all of the basic commands are very fast (at least if you remember to specify a different temp directory than /tmp). In addition, the vast majority of all bioinformatics software today is designed to work within a unix framework and conform to the Unix “way of thinking”. The Unix framework is the one thing that makes the proliferation of software that we see today possible. Without that framework, we would all be stuck in our own tiny worlds working with a small toolset designed to only work for that particular problem. The mix-and-match opportunities that we have today would not have been available to us.

101. IUPAC describes a set of 18 single-character nucleotide codes that can represent a DNA base: which one best reflects your personality?

I think I’ll have to go with Y, because that is the question I can never stop asking.

Updated 2014-11-14 11.17: Clarified that position at NSC is no longer current but that she instead has a part-time position at the NVI.