Breaking the interdisciplinary ice
I remember reading the following sentence in the announcement of my current post-doc position as part of the dCod project: “The work will involve close collaboration with research groups both from biology and from mathematics”. I thought it was an interesting ambition, but I wasn’t sure how close would this collaboration be and how would it be organized. I guess the scheduled biweekly dCod meetings were the first hint.
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FADE IN...
A dCod meeting back in November 2016:
BIOLOGISTS
Precision-cut liver slices... cytochrome P450...
pxr... estrogen receptors... PPARs...
MATHEMATICIANS
Topological data analysis... persistent homology...
cycles... model reduction...
BIOINFORMATICIANS
Co-expression analysis... network analysis...
feature selection... omics data integration...
It was obvious that we needed a common language to cooperate. That required time, efforts and different kinds of activities from everyone in the consortium. We found ourselves in an iterative process, in which we go back to the basics when explaining a concept or presenting a method. “Can I ask a silly question?” is a phrase I, as a bioinformatician, still repeat to either the biologists or the mathematicians during dCod meetings. The simplified answers to those questions are like keys that unlock the boundaries between our fields within this project, towards understanding the complex systems toxicology of cod. These interactions not only help me comprehend what other project members do, but also push me to reflect on what I do and how to present it. It is inspiring to learn how this became a common way of thinking and I look forward to seeing it translated in our publications.
Recent technologies can generate large-scale data in a revolutionary way. Still, why don’t we have suitable means to monitor the environment? Why don’t we understand the causes of many diseases? Countless questions can be raised. From reflections and realizations on these issues, terms like inter-disciplinary, cross-disciplinary, trans-disciplinary research became familiar. Even though concrete definitions of these words are still debatable depending on the nature and practice of interactions, they all share the notion that distances among disciplines needed to be reduced to some extent. In general, operating in a conventional way may seem easier and safer. For instance, biologists have a dataset that they present to mathematicians and bioinformaticians on separate occasions. Each group analyzes it and provides different, and sometimes overlapping, insights on the data. In contrast, having biologists, mathematicians and bioinformaticians sit together and discuss an experimental dataset may look challenging and risky. Yet, the potential of each study lies in the ability to understand its context, its settings and its purpose, in addition to the capability to identify the right analysis approaches that could uncover valuable information it potentially holds. So, why not start by discussing experimental settings? Why not maximize data mining outcomes by thinking together about the optimal way to use available resources and competencies? During earlier dCod meetings, it didn’t occur to me that at some point, I would be part of an experiment planning session. But yes, there I was, and it wasn’t awkward! Branching out from these discussions, was a series of in-depth conversations with the mathematicians on data integration in the context of network biology and topological data analysis. Last year included cycles of meeting, reading, coding, and testing how bringing these two areas together can contribute to the analysis of experimental data. I am very happy to see this collaboration finally rendered into a novel gene expression analysis approach.
Interpretations may differ on {multi, inter, cross, trans, ...}-disciplinary research. Nevertheless, my observation is that the dCod project is evolving through these terms in their increasing order of cohesiveness, irrespective of their strict descriptions. In the end, for different disciplines to converge, we need to dare ask those “silly” questions!