Systems Control Group

The Systems Control Group

From left to right: Zuogong Yue, Vladimir Levin, Junyang Jin, Sofia Pereira, Beatriz Garcia Santa Cruz, Mehri Baniasadi, Atte Aalto, Laurent Mombaerts, Jorge Gonçalves, Johan Markdahl, Stefano Magni

About the Systems Control Group

The Systems Control Group (SCG) collaborates with biologists and clinicians to improve our understanding of diseases, with the goal to develop new therapies. The group produces theoretical and computational methods to achieve the goal of identifying how diseases arise and how they are mitigated. A key part is to build mathematical models that help pinpoint the locations and underlying mechanisms of diseases. The models capture an important feature of biological systems: the fact that they change over time in response to internal or external stimuli. The group focuses on developing methods for working with time-series data, as we predict it will become increasingly significant in future biomedical research. Time-series data consist of snapshots of system properties at different time points, such as molecular concentrations of RNA, proteins or metabolites. While time-series data is more expensive to produce than steady-state data, tracing a system’s transient behaviour provides essential information about how different molecules interact with each other. Bringing together diverse backgrounds in mathematics and computational sciences, the members of the group engage with this overall problem from different perspectives. Current initiatives include developing methods for inferring causality in gene regulatory networks, and pinpointing the source of perturbations or diseases from those networks. The group collaborates closely with biologists and clinicians to develop mathematical models with key predictive powers that are subsequently experimentally validated. This ensures that the group’s research has broad-ranging applications within biology and biomedicine, including Parkinson’s disease (PD), deep brain stimulation (DBS), mechanisms of circadian rhythms and stem cell differentiation.