In a brief communication arising published Oct. 20 in Nature, Dr. F. J. Müller, CAU Kiel, and Prof. A. Schuppert at AICES, RWTH Aachen, show that today's established high-profile approaches (1) for systems control are severely limited in their generalization for the control of biological systems (2). This finding has direct implications for biomedical research and its current applications such as in the field of stem cell biology.
The German researchers propose that a future control theory for biology must cover self-regulation features of living cells resulting in a significant reduction of dimensionality observed in empirical data. These often underappreciated features of biology unfortunately cannot be sufficiently explained and utilized by the established control theory approaches. In their response to the points raised by Müller and Schuppert, the respected group around Albert-Lazlo Barabási states consequently on their general control theory: "our [previous] result hides subtleties that reveal as much about controllability as about the limits of our current understanding of biological networks" (3).
Schuppert explains: “In order to fully control a system—say for example a stem cell scientist wants to differentiate a stem cell into dopaminergic neurons, the type of cells, which are lost for example in Parkinson's Disease—the researcher ideally needs to ‘fully control’ the biological system. Following the current state-of-the-art control theory concepts, one would need to drive nearly all genes in such a process towards the desired cell population, something that’s basically impossible to do in reality.
"Evidence in the field and formalized by us, draws a completely different picture: We have very good reasons to believe, that only a few, cleverly chosen inputs can fully control and drive for example stem cells towards becoming the ‘perfect’ therapeutic agent. The key question is now, how can we find this ‘perfect linchpin’ for exerting full control over a biological system–and that’s what we are working on right now!"
This cutting edge type of research will be further pursued in a close collaboration between the systems biology expert Schuppert and the stem cell biologist Müller.

• 1. Liu, Y.-Y., Slotine, J.-J. & Barabási, A.-L. Controllability of complex networks. Nature 473, 167–173 (2011).
• 2. Müller, F.-J. & Schuppert, A. Few inputs can reprogram biological networks. Nature online (2011).doi:10.1038/nature10543
• 3. Liu, Y.-Y., Slotine, J.-J. & Barabási, A.-L. Reply to Müller and Schuppert. Nature online (2011). doi:10.1038/nature10544