It was a gradual development, but I've always been interested in science. As a child, I read facts about dinosaurs and subscribed to Science Illustrated. Life has always fascinated me – it is the most complicated thing there is. To gain insight into that, has always fascinated me.
When I started studying at NMBU, I knew what I wanted and went straight into bioinformatics. I am perhaps one of the few who chose bioinformatics on admission. I knew that I wanted to study bioinformatics because of the good opportunities it gives if you're interested in biology and technology. With bioinformatics you have the opportunity to perform data analysis yourself, and you're not dependent on others to do it for you. There are so many exciting things to investigate. The biology is what's exciting – but the mathematics and programming are also cool and creative.
When I was completing the prerequisite subjects to apply to university, I had to do math. So I decided to figure out what I had misunderstood with math, because ever since grade school I'd thought 'no, this is apparently not my thing'. A few key pieces fell into place with a more thorough approach, and suddenly I could do math. That meant that I was no longer afraid of it – and so majors like bioinformatics were not as scary anymore.
Why did you choose to take a master's degree with BIAS?
When I started at NMBU, the university had just changed its name – it's in the name, Bioscience. Here, the focus is on biology, programming and statistics – very applied, direct and practically oriented towards biology. There are bioinformaticians who first and foremost study programming, and there are biologists who have learnt programming by themselves. The opportunity exists to also carry out some of the data collection oneself, as we have lab courses in addition – not just programming. My hope is to become a person who has an overview over all aspects of research: from data collection to processing to working with methods for extracting biologically interesting data that you can work with.
How would you describe your time as a student?
I think it's been very nice. When I first arrived here, we had Welcome Week. It was also an UKA-year, so altogether there was a lot going on. I became the student representative for BIAS on the faculty's Academic Affairs Committee while I was doing my bachelor's degree. There was a student meeting where we were going to get information – there was supposed to be a student representative from the faculty's Academic Affairs Committee there to talk about the master's degree – but there was no one there, so then it became 'you've chosen this, would you like to be the representative?'
I've not been a member of any clubs, but I've been webmaster for Molekylet, the student association for the Faculty of Chemistry, Biotechnology and Food Science (KBM). This involved reviving the webpage – so we made a new one. I was also on the board; we organized Christmas parties, spring parties and a few other things – game nights for example. These activities are for all students at KBM. Like other student associations, Molekylet arranges Welcome Week for new students. One of the board members becomes coordinator for new students for the faculty. Student life is absolutely social when you're part of that.
In addition, I've been a teaching assistant for BIN210, STIN100 and BIO101. It's been both challenging and fun. I recommend that everyone gives teaching a try.
We're interested in how microorganisms communicate and become a part of the salmon's biology – how they're important for development. My thesis is mainly about the role of microorganisms in the salmon intestine – to understand which bacteria and genes can be of interest to study further.
The data originate from a long-term feed experiment, where they've fed salmon different types of feed: some containing omega 3 and others not. When salmon is in freshwater, it can make its own long-chain fatty acids, but it loses this ability in the ocean. The transition from freshwater to saltwater also influences the intestinal bacteria. There's actually quite a lot going on in this dataset.
I use network analysis to reduce the number of dimensions in the data to a level that is possible to handle, a level that actually makes it possible to generate new hypotheses. You start with 32,000 genes after a little filtering, more than in a human – that's too much to look at. So I take all the gene transcripts, and all bacteria that we've measured, and try to find groups of genes and groups of bacteria that behave in the same way with respect to gene expression and abundance. That reduces the scope down to something like 25 groups. Then you have quantitative data on how they behave, how they change, on an overall level.
These are simple, linear models – it's not supposed to be very complicated. There is already an existing R-package, and this is just a natural extension of that. I've not seen anyone else doing exactly this.
We humans, if we do not have a good combination of bacteria, may become ill – the intestinal system may not work properly. We are literally surrounded by bacteria and dependent on them, and the same is the case for many animal species. But then it's important to find out which relationships are special, and which relationships are general, per species. There have been many studies done on mice and humans, but not so many on animals in aquatic environments and very few on fish. That's why it is interesting to study animals like salmon; salmon is interesting, and it also has economic value for Norway.
I would say that this group is very cozy. We have quite a few BIAS group meetings, where lunch is included. It's smart to be a part of this from early on, get to know the people here, take advantage of your access to professors, get to know them, talk to them. If you start early you can ask questions about a possible thesis study – it may be that there's lots they'd like to work with. Don't decide on a particular thesis study early on, but do start early with communicating and asking questions. Get some insight – you have to be exposed to possibilities before you can make a good choice.What are your thoughts for the future? What would you like to do?
I would like to do research – it's what I’ve wanted all along. That's where I see myself, so we'll see if that's where I end up. It would be very interesting to learn more of the math that is behind the science, but also more of the biology. I have thought to apply for a PhD that is being announced. My intention is to continue on this path.Do you have a favorite concept from your field that you'd like to share?
The concept of whole genome duplication, which applies to salmon. I've always been a fan of evolution, and one of the concepts which may be difficult to understand within evolution is how gradual change, even when it's understood on a molecular level, can lead to completely new traits in animals. How development can happen so fast – even if it takes millions of years, evolution can happen quite fast now and then.
The idea of whole genome duplication – and it's a quite simple idea – is that all cells have to split in order to become two new cells. That's a fundamental part of being a cell in itself. Then you have to copy DNA, and if one cells keeps all the DNA, then you suddenly have double the number of genes. It is of course a little more complicated in animals with sexual reproduction, but the basic principle is there.
That process of having everything duplicated – it's like having a garage with tools and a stack of materials, and then suddenly you get a new garage with new tools and materials. You can build what you were going to build, and then suddenly you can build something completely new in the other garage.
It seems so much more understandable how things hang together – and that's what I love about biology. But to learn about biology in this way you need bioinformatics; it gives you the tools to understand much more about what we observe in nature.
- Interview edited for clarity and length.