Strength In Numbers: Finding And Developing Bioinformaticians
With the eruption in ‘omic’ data, there aren’t enough people with the necessary skills to translate it into applicable knowledge.
Fast, affordable, sequencing is almost single handedly responsible for bringing about a new ‘genomic era’. New sequencing applications are looking outside of the the lab, into the clinic, and beyond. Illumina President, Francis de Souza, has been quoted saying he estimates 1.6 millions genomes to be sequenced by 2017. Those kinds of numbers make it difficult to remember a time when availability of useful genomic data was quite scarce, even if it was a relatively short time ago. There should be some very interesting patterns hidden within that richness of data. But the crucial point here, is to generate findings that are significantly different to what has already been found. To find something new.
An Encouraging Sign of Change
Building algorithms to transform high-dimensional functional genomics data into interpretable patterns, is fundamental to the success of a true ‘genomic era’. Michael Hoffman, of the Princess Margaret Cancer Centre and University of Toronto, is one of the men leading this field today, with particular interest in epigenomics. He raised two challenges facing bioinformaticians today- the lack of a standardised data format; and “finding enough people who can do this stuff”. Both issues have been echoed throughout academia and industry.
The lack of bioinformaticians is not a cause for concern. It is a very encouraging sign of change. Bioinformaticians have been around for decades. The first biological databases were being built shortly after early protein sequences began to be published in the late 1950’s. Since then, the amount of ‘omics’ data has grown at a staggering pace. The limiting factor now, is that technology has improved so quickly that the labour force hasn’t quite caught up. Where once, bioinformaticians were a specialist breed, holed up in a rarely visited basement, they now find themselves one of the most sought after units of any research centre.
The role of a bioinformatician has developed from database creation and curation, to code-writing-genius. The amount of -omics data available is intimidating enough on its own. Add in the contextual ‘real world’ data and clinical trial data, and it becomes very easy to get lost. Elaborating on Michael Hoffman’s call for “people who can do this stuff”, you need people with the fundamental creativity, ingenuity, and curiosity, to know why to look, where to look, and how to look.
The Next Generation Of Research
Universities are starting to develop specialist programmes in an effort to develop this skill set in people, through interdisciplinary collaboration. University College London’s CoMPLEX (Centre for Mathematics, Physics and Engineering in the Life Sciences and Experimental Biology) is an eye catching example. Here, MRes and PhD students are supervised by a cross departmental team drawn from life sciences and mathematical/physical sciences. Students are given a founding education across the range of sciences and computational methods they will be exposed to, but the main focus is on developing interdisciplinary research skills.
Interestingly, students from CoMPLEX typically remain in research following completion of their PhD. Their skills are in demand, and have crucial experience across a breadth of applicable sciences. This is in contrast, to ‘domain specific PhD graduates who often look outside of research to make their mark on the world.
Centres like CoMPLEX, show that leading institutions recognise the importance of finding innovative approaches to scientific discovery. Which is indicative of how research in the life sciences is changing. James Kobielus, IBM’s Big Data Evangelist, believes “computational tools accelerate discovery, if applied correctly”. They are becoming an increasingly significant aspect of research, with Kobielus predicting that “a computational method will win the nobel prize [in physiology or medicine] in the next few years.”
With the eruption of genomic data showing no signs of stopping, it is hard to argue against that prediction. The lack of bioinformaticians, is not due to dwindling numbers. It is an indication of how crucial they are becoming.
This poses two questions.
- How do we cope with the shortage of bioinformaticians today?
- How do we find and attract the right people to pursue it as a career?
Answering the first question is easy, in principle. Education and training. Any scientist has to have a healthy sense of curiosity and love of learning. With such a strong background in their own domain, taking a proactive step towards learning how to use some of these computational tools would help tremendously. And of course, this is something that already happens quite often. However, it is a process that takes time. Particularly in industry, time is often a luxury that few can afford.
So rather than trying to develop the skills that allow you to take on bioinformaticians work, a very quick fix would be to learn what you can do, to help save bioinformaticians time. This takes us back to Professor Hoffman’s frustration at the lack of a standardised data format. If you are generating data, try to find out how it needs to be captured and formatted. If you are looking to compare against a reference genome, take the time to understand it and what it includes, so you can provide useable data.
Silos are a terrible phenomenon wherever humans work. In this instance, clear communication and understanding between research scientists and bioinformaticians, at the start of any project, could save both a lot of time, effort and open up some more bandwidth. In the long run, it may result in both parties learning some transferable skills along the way.
Bioinformatics In Schools
Thinking ahead, the number of bioinformaticians needs to increase. For many, the first touch point with bioinformatics comes briefly or late on in a bachelors of science degree. By this point, you may have already lost many potentially great bioinformaticians. The modern day classroom, let alone lecture theatre, sees less and less pencil and paper. Technology is changing the way people learn. From hardware like, laptops and tablets, to open source software and the internet, today’s learning environment is very different to what it was just ten years ago. Introducing students to bioinformatics much earlier in their education, may just be enough to help engage them. That’s not to say that all tech-savvy school children will suddenly have any affinity for bioinformatics, but there may be some that find it interesting enough to pursue from a younger age, as opposed to working in the financial sector.
The Genomic Frontier
“Science is exploration. A Journey that has no end. What you’re looking for may never appear.” These are wise words once more, from Mr Kobielus. Unfortunately, professional pressures can force one to abandon that principle from time to time. But genomic data is presenting an incredible unchartered, frontier of exploration. That alone should be enough to excite any scientists, computational and biological, to develop the necessary skills to strike gold and win that historic Nobel Prize.