Abstract
Systems biology is a research program that aims to predict the function (and failure) of organisms, considering all relevant length and time scales, based on the solution of a system of n ordinary differential equations. Of course, n will be a very large number. Surely, the successful technique will involve many interesting opportunities for order reduction, purely mathematical, and on the (bio-chemical) recognition of invariant superstructures, so that n will not always need to run over all participating molecules. The community of systems biologists is working very hard to complete the task of building relevant equations that can be solved, and on establishing efficient algorithms to do the computations.
The outcome of such numerical experiments will have to be verified, and it is questionable whether judging the outcome of macroscopic observables will provide enough information. More than that, the solvers of the system will require sensible initial conditions to start off simulations, rate equations for all relevant molecular interactions, and intermediate state variable checkpoints to judge the quality of the evolution of the (nonlinear) system. In principle, we need to access the instantaneous metabolic data. To date, no sensors exist which can provide this information at the cellular or organism level, which is in stark contrast to similar activities for macroscale complex systems (such as for chemical refineries), where microsensors can almost non-invasively report relevant data and hence support the model builder.
The idea to help close this gap has captured my imagination, and to a large extent is driving my current research effort. I am focusing on a technique called nuclear magnetic resonance (NMR), well known from magnetic resonance images (MRI) of the inside of the body, and working on miniaturizing this technique using microsystems technology, and making it more precise and sensitive, so that it can be used to deliver exactly that information that systems biologists need to capture the metabolomic state of a biological system with chemical precision. It is an engineering task, for sure, and involves a very broad number of disciplines in a dedicated team to make progress. In my talk I will show what we have planned to do, how the disciplines are interacting, and how far we have come to date.
Biography
Jan G. Korvink obtained his M.Sc. in computational mechanics from the University of Cape Town in 1987, and his Ph.D. in applied computer science from the ETH Zurich in 1993. After his graduate studies, he joined the Physical Electronics Laboratory of the ETH Zurich, where he established and lead the MEMS Modelling Group. This was followed by a move in 1997 to the Albert Ludwig University in Freiburg, Germany, where he is Professor for microsystems engineering and runs the Laboratory for Microsystem Simulation.
Dr. Korvink is a curatory board member of the Fraunhofer IPM laboratory, and hence a voting member of the Fraunhofer Society. He is a Research Advisory Panel member for the Council for Scientific Research (CSIR) in South Africa. He is a steering committee member of the International Research Group -Nano Micro Systems- (NAMIS).
Prof. Korvink is author or co-author of more than 200 technical publications in the broad area of microsystems. He has written a textbook, numerous book chapters and edited volumes. He is a founding editor of “Advanced Micro and Nano Systems”.
He is a technical programm committee member for numerous conferences, and is a member of ASME (http://www.asme.org) and the Design Society (http://designsociety.org). Prof. Korvink was guest professor at the ETH Zurich, Ritsumeikan University in Kusatsu, Japan, and guest scientist at Kyoto University in Kyoto, Japan.
His research interests cover the development of ultra low cost micromanufacturing methods, microsystem applications in the area of magnetic resonance imaging, and the design and simulation of micro- and nanosystems.
Since July 2010, Prof. Korvink is appointed as Visiting Professor of Electrical and Computer Engineering at the University of Virginia.