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Complex Living Matter

Institute of the Science of Complex Systems

Artificial Cell

We see life as a self-sustained and self-regulating consecutive evolution of ‘genetic activity’. Which gene ‘activates’ or silences an other is governed by the genetic regulatory network (transcription network). This network governs the production and decay of RNA, proteins and other nucleic material. We simulate these processes in a computer model of the cell. We try to understand emergent dynamics of such artificial living systems, such as synchronization (origin of cell cycle), stability, differentiability (under which stimuli will a cell of certain type-switch to an other cell type), robustness and adaptability (how does a cell adapt to changes of environment).

Genetic regulatory networks are not known in detail. In our studies we work with artificial (random) networks. In a set of other studies we try to gain insight in the nature of real Gene Networks.


We try to infer the structure and detailed topology of genetic sub-networks, e.g., related to specific pathologies. We start from ‘omics’ data, such as gene expression profiles from a multitude of experiments, and reconstruct the networks which explain best the whole set of data. We employ methods from network theory, Bayesian reasoning, and optimization techniques.

Biological Time-Series

Interactions between and combinations of biological systems may lead to complex regulation phenomena. Some of these are reflected in time-series, which often contain information both on the function or state of the sub-processes and on the quality of the interactions. We try to use the ‘structure’ of these complex time-series to disentangle the different states and their functioning. From this we can sometimes detect ‘abnormities’ indicating either pathological conditions, or structured information. In particular we have been looking at:

  • Heartbeat time-series to detect signs of heart failure
  • Time-series of fMRI blood oxygenation levels to detect location, correlation and quality of brain activity
  • Cell motility to identify propulsion modes of e.g., metastasizing cells
  • Correction movements of human gait to test the function of vestibular system and disentangle it from other gait components