Gaining an understanding of bioinformatics is now par for the course when it comes to training undergraduate students in biology. However, facilitating a comprehensive course in bioinformatics is often hampered by the constraints of a typical classroom environment, specifically the software and hardware requirements. To grasp more in-depth concepts, beyond what is offered from basic tools available online, Daniel Barker from the University of St Andrews, UK and colleagues propose the re-creation of a bioinformatics research environment. To this end they developed the 4273π platform for teaching bioinformatics, on the inexpensive Raspberry Pi computer, modified for the classroom setting and including their Open Access bioinformatics course – as explained in their recent study published in BMC Bioinformatics. Barker and leading bioinformatician Ian Korf from University of California, Davis, USA discuss the importance of bioinformatics training for biologists, and the potential for 4273π to improve the way this is implemented.
Why is teaching bioinformatics so important now?
IK The main reason is that biology is becoming much more quantitative. Sequencing and other high-throughput technologies are revolutionizing many biology-related industries. In the past, people would focus on a few genes, for example, but today it’s possible to look at all genes. That’s a very powerful paradigm, but you need a different ‘microscope’ when looking at genomic data, and it takes some training to understand how to handle and analyze large data sets.
Biologists are adaptable people in general, and I find that the typical biologist can become a good bioinformatician. Many would-be bioinformaticians get scared away because of the arcane syntax of the command line, their lack of computer programming experience, or a feeling that their mathematics skills are insufficient. These are just fears. If you hold their hand for a little while they can get through the scary bits, they will emerge on the other side self-empowered and with a new perspective on problem solving. It will impact everything from grocery shopping to genome analysis.
What are the challenges in organizing an undergraduate bioinformatics course at a university?
IK Most universities have plenty of computers, but they aren’t typically configured to analyze genomic data. Most bioinformatics takes place in a Linux/Unix/Mac environment yet most labs have Windows boxes. It’s easy enough to install Linux on a PC either as a second OS or in a virtual machine, but the University might not want to do that and may have policies against it. So one solution is to have a separate set of Linux machines for bioinformatics. That can get expensive. Once you have the computers, you have to set them up with an appropriate bioinformatics environment too, and that can be complicated by the ever changing nature of the field.
DB At my university, the computer classrooms run Windows, which is one of the least useful operating systems for bioinformatics. A few years ago we used the Windows computers only to log in to a remote Linux server, but this still has limitations and isn’t much fun. Students are denied administrator access – so they are more dependent on staff, to install software and so on, than would be likely in a subsequent career.
I have not found costs to be a big problem. Laboratory practical classes in other areas of the curriculum can be expensive, requiring consumables and technical preparation every time they run. For bioinformatics, equipment has to be purchased every few years but the intervening years are much cheaper.
IK One of the greatest obstacles to teaching bioinformatics is the teachers themselves. Bioinformatics is an eclectic field drawing from molecular biology, statistics, computer science, mathematics and other disciplines. Not many teachers have such a diverse education.
DB Another problem has been textbooks. There are plenty, but it has been hard to find anything with the right balance. I was very happy when ‘UNIX and Perl to the Rescue’ came out (Keith Bradnam and Ian Korf, 2012). It covers the underlying skills well. Still, it is not intended to be a complete bioinformatics textbook.
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