There was a time in humanity’s history where it was possible to know everything, but that time came and went as the collective knowledge pool continued expanding through novel academic achievement. Whilst the question of who could be considered the last person alive to truly know everything is a fascinating one that would easily merit an article of its own, I’m here today to write a few lines about a consequence of the constant development of our understanding of the surrounding reality – heavy knowledge specialisation.


Figure 1: The specialisation of knowledge of a particular individual through a fragment of his academic career, as per PhD comics.

In order to address the issue at hand, let’s define knowledge specialisation first. Look back to your school days. You’d run laps in gym class, you’d draw pictures in art class, you’d learn the basics of science, literature, mathematics, and history. The curriculum was about as broad as humanly possible, and it only got narrower from there. As exams passed, the focus of the curriculum shifted towards a handful of subjects, arming you with more knowledge in those fields. Given the fact that you’re reading this, it’s pretty safe to assume you’ve got some level of interest in science, so it seems probable that you followed that path. You don’t run laps or draw pictures anymore, instead pursuing knowledge related to the field of your choosing. This just keeps deepening as you continue your education, with the time stretch from undergrad to PhD illustrated in a PhD comic reproduced in Figure 1. The reason for this is simple – today, our knowledge is so vast that you have to get extremely specific to acquire a sufficient depth of understanding to enable constructive participation in further broadening our understanding of a given phenomenon.

Another thing that changed since the day when it was possible to know everything was a shift towards a more team-based research dynamic in a number of science fields due to developments in technology and knowledge. Scientific collaboration is of the utmost importance as it enables tackling problems of far grander scope, and combining the expertise of individuals involved in the project. As a practical example, the Human Genome Project saw 20 universities worldwide join forces for over a decade to sequence over three billion base pairs making up the human genome in a time where sequencing technology was in its infancy, a scientific accomplishment of magnitude unthinkable back in the days of van Leeuwenhoek looking at microbes through fancy magnifying glasses. Scientific teams often feature a number of members, who are experts at different fields that come together to pose the underlying research question the team is tackling, and an element of being interdisciplinary makes it possible for them to communicate and effectively move the project forward.

So, what does being interdisciplinary constitute? It’s the ability to reach outside your primary field and acquire some expertise in relevant, but unrelated subject matter. The beauty of the expansion you’re performing is that you’re not obliged to obtain the same in-depth level of understanding as true experts in the field, but the knowledge you gain will enable you to apply relevant elements of the field in your work, as well as communicate with the experts. Communication is the driving force of interdisciplinary collaboration – my parents were present during the establishing of scientific relations between local teams of oncologists and statisticians, and they recollect that at first the joint meetings ended with the two parties walking away understanding absolutely nothing of what the other one was trying to say. It took quite some time for the groups to find a common language, but once communication became more effective the collaboration blossomed. It’s extremely important to communicate your science in a manner that is going to be understandable to the non-expert, leave out the technicalities and focus on the take-home message and crucial points without talking down to them. If relaying an experiment to a data analyst, focus on crucial elements of the experiment design that may prove vital in modelling. If relaying back the statistical analysis, let them know the exact hypotheses used in testing and the conclusions that can be drawn.

I’m a product of the times – the creation of interdisciplinary collaboration bred opportunities for interdisciplinary education, and that’s the path I’ve been pursuing. Whilst I don’t get to run laps anymore, and the only picture drawing I do is making figures, my undergrad was a collaboration between three departments that filled the curriculum with chemistry, biology, computer science, modelling, and environment protection. Whilst none of those were dealt with in great depth, they did offer me a broad and varied foundation from which to start my PhD, which in turn is a blend of data analysis, computer science, biology and statistics. The interdisciplinary crosstalk gets funnelled directly into my work – the backbone of my PhD project is the development of an exploratory algorithm called WIGWAMS, which identifies genes exhibiting co-regulation across a number of independent datasets. WIGWAMS sees the fusion of the different component fields, as the large scale data is utilised in a statistical framework to answer the biological question of discriminating between co-regulation and genes exhibiting similar behaviour without an underlying regulatory backbone. The combination of the components makes it possible to discern between those two phenomena in a manner not possible for other algorithms capable of operating on that kind of data.

It should be noted that the collaboration aspect so deeply ingrained in the interdisciplinary life is a double-edged sword – following an interdisciplinary upbringing turns us into Jacks of all trades. I’d view my algorithm design and programming skills as my main fortes, but I’m aware that my ability is lesser than that of computer scientists with proper training. Going back to Figure 1, our dot ends up being a bit higher up on the line than someone with a dedicated and more focused training in any of the fields we cover, and there are always going to be people more qualified in those individual fields. Nevertheless, there is ample room in the world for interdisciplinary people due to their all-around competence and ability to communicate with experts in different fields. This in turn makes collaborations immediately fruitful and reduces the time needed for experts in unrelated fields to find a common language to communicate with each other.