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Professor of Molecular Systems Biology (em), ETH Zürich, Switzerland

Main research aims? The main research aim of our group has been to develop analytical techniques to understand the molecular basis of the phenomenon “life.”

Biggest challenge facing the field? The biggest challenge in the analytical sciences applied to biology and medicine is the lack of a paradigm to position measured analytes such as nucleic acids, proteins, metabolites and lipids in the context of living systems. Progress in the analytical sciences has catalyzed amazing progress in detecting, quantifying and identifying biomolecules as chemical entities to a degree that essentially any biomolecule can be detected, many even from single cells. Yet, a collection of molecules is not sufficient to create and sustain a living cell. We are presently lacking a general concept of how the detected molecules have to be positioned spatially and in relation to each other molecules to constitute a living cell and generic analytical techniques to systematically extract this essential contextual information.    

Most exciting trend today? Apart from the exciting technical advances in analytical science which continue unabated, to me the most exciting development is the convergence of analytical and computer science. The work our group has substantially focused on is the analysis of proteins as molecular entities consisting of a string of amino acids, at times further modified or processed post synthesis. The convergence of analytical and computational methods now make it possible to computationally extrapolate from the results generated by analytical techniques focused on the proteome to extrapolate to the structure, function and cellular context of the detected molecules, thus moving the analytical techniques closer to understanding biological processes and phenotypes.   

A problem that could be tackled interdisciplinarily… The fundamental problem in molecular biology and medicine, how the molecules that constitute a living organism and their properties, attributes and interactions determine phenotypes. Solving this problem can only be achieved through interdisciplinary  work minimally involving biologists/clinicians, analytical scientists and data scientists.    

Most memorable advice? Don’t take critique or rejection of your ideas or work personally, do the best to convince the peers and if you do not succeed move on. (Advice from Lee Hood.)