Bioinfo what?

So I thought I’d spend some time explaining a little more about the field of Bioinformatics.

If you wikipedia it you will discover that it is where statistics, programming and biology meet. You may then be wondering when would this happen? Although the relevance of maths in biology has been present ever since its first outing, the need for mathematicians or programmers is much more recent.

It has mainly arisen as technology has improved to produce ever-increasing amounts of data, and more complex data at that. In 1990 they started sequencing the first genome, finishing in 2003. These days, the data can be generated and analysed in around a day. Whats more we can now generate data on not just the genome, but the epigenome, transcriptome, metabolome and proteome. These are collectively known as the ‘omics. What they all have in common is lots of data points (generally hundreds of thousands) each representing different parts of your DNA or the resulting chemical molecules.

It would be completely implausible to try to analyse each data point one by one with a pen and paper. Therefore, some knowledge of programming is needed to manage the data and implement analyses efficiently.  The role of statistics is to ensure that the data is analysed appropriately and results are not chance findings. While the biologist is needed to run the experiment and do the interpretation. This is a simplication of how these skills come together, but there is huge variety in the type of projects requiring a bioinformatician.

Bioinformatics is now a field in its own right. I am not aware of any undergraduate course in the UK, although many bioscience departments are starting to offer modules in it. Often the first chance you would have to study it is at a masters level. Courses will accept biology, mathematical/statistical or computer science graduates, but my experience is that the vast majority of the intake have studied biology or related disciplines. I mainly put this down to no-one telling mathematics or computer science undergraduates that this is an option, as these course are predominately based in bioscience or medical schools. It may also be that biologists realise that to remain competitive in the jobs market you need to have some of these skills (particularly if you want a career in genetics). I have seen non-biologists initially really struggle on these courses, as it is a steep learning curve from GCSE or A level  with lots of new vocabulary, concepts and mechanisms to get your head around. It can be demoralising and seem like a daunting task, but when it comes to the analysis side you will find the tables flipped and everyone looking at you wishing they could do what you can so it is worth being patient and sticking with it.

So if this appeals you are probably wondering, which of these subjects should you study at undergraduate level? Well, as all of them can lead to the same outcome it has to be a choice based on were you think your strengths lie, what you will enjoy, and remain motivated to study for three or more years. What I would say is look for opportunities to broaden your skill set across the three domains, can you do a computer science module or learn some programming as part of your final year project in your Maths degree. Does you department offer a bioinformatics or mathematically modelling module in your biology degree? Can you develop some software to help a field biologist collect and store their data. My break came when I spent 10 weeks doing a computational biology project in Edinburgh during the summer of my Maths degree. This was my first chance to learn to programme and learn about the data biologists were working with.

The reality is that most bioinformaticians have a particular strength and positions call for different combinations of skills. You may not need to be the whizziest programmer but have a good analytical mind to decide which statistical approaches should be used. You may not know a huge amount about what the data is but you do know how to store data in an efficient and secure manner, or how to set up and manage high-powered computing systems.

Which ever way you approach it you will have many opportunities to work on different projects with different teams all over the world. Almost all industries are increasing reliant on data and informaticians to stay ahead, so if you decide that biology isn’t for you there are many other opportunities out there with these skill sets, so it worth thinking about!

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