Jakob Ruess – Co-Laureate of the 2012 SIB Best Swiss Bioinformatics Graduate Paper Award
Jakob Ruess received the award together with Christoph Zechner as co-author of the publication “Moment-based inference predicts bimodality in transient gene expression”. The paper was part of Jakob’s graduate studies in the team of John Lygeros at ETH Zurich.
Jakob now has a permanent Group Leader position in France. His team is affiliated to both the French National Research Institute in Computer Science and Applied Mathematics (INRIA) and the Center of Bioinformatics, Biostatistics and Integrative Biology (C3BI) at the Pasteur Institute in Paris. One of the key aims of Jakob’s research is the development of mathematical models that can be used to represent, understand and eventually control the dynamics of biological systems. To learn more about his research interests, visit Jakob’s group webpage and read our interview.
What do you like to do in your free time?
Honestly, I feel like becoming a scientist means also that it becomes increasingly hard to cut clear lines between work time and free time. Is the time that I spent answering this question work or free time? So let me answer this by saying that when I am not sitting at my desk, I enjoy discussing over lunch, a beer, or coffee the scientific, political, societal, ecological (and what not) state of the world with my colleagues and friends who come from all corners of our planet and who often have very opposing opinions. Lately, I have also been reading quite a few French books, since after all it is useful to learn the language of the country in which you live. When I go on holidays, I usually try to go somewhere quiet to escape the busy Paris for a while. Unfortunately, the Alpes are a bit further away than they used to be during my time in Switzerland.
Any words for the future generation of bioinformaticians?
In science in general, and maybe in biology and bioinformatics in particular, there are always some topics that are very trendy. There is nothing wrong about a topic being trendy. There is usually a good reason for this, for bioinformatics it is often that a certain type of data is widely available and the need for methods to analyse such data increases. Yet, what we do sometimes forget is that experimental technologies are evolving at a mind-boggling speed. So when we develop methods, we should also take into consideration what kind of data will likely become available in the future since otherwise our methods are always lagging behind the needs of biology. And to go yet a step further, I think that analysing data is not the only job of a bioinformatician. We also need to contribute to figuring out what data would be required in the first place to allow us to resolve open biological questions. This implies that we should actively involve ourselves in the development of experimental technologies or at least ensure that we have very good communication channels with people working on these things.