Centre of Excellence in
Computational Complex Systems Research


Our research focuses on understanding complex physical, biological, cognitive or societal systems and their behaviour. For this purpose we do computational analysis and modeling. In addition, we do simulations based on data collected by selected experimental methods. The research is conducted cohesively in four mutually supportive fields of Models and Methods, Engineered and Artificial Systems, Cognitive and Social Systems, and Computational Systems Biology. For more information see the Annual Report 2007.

Models and Methods

The main role of the Models and Methods research line is to facilitate the research activities of the other groups of the CoE. The focus is both on "fundamental" as well as "applied" research. The former comprises theoretical and numerical work on mathematical models of complex systems. In the former, one focus are is complex networks, which are rapidly becoming a standard framework to analyse and understand complex interactions. In the latter, we will focus on computational tools and methods required for analysing and understanding experimental data, such as state-of-the-art statistical modelling methods (e.g. Bayesian modelling), with applications in several fields, in particular brain signal analysis and bioimaging.

Engineered and Artificial Systems

Modern technology research is building novel artificial systems. In nanotechnology this emphasises the need to understand the fundamental behaviour of materials (solid, soft or biological) and devices, which show intrinsic complex phenomena such as pattern formation, self-organisation and self-assembly. These nanoscale systems are well-suited for computational modelling studies, which form the basis for applying them in nanoscale bioinformatics, biomedical analysis and in imaging systems. In the area of information technology, we develop computational models of cognitive functions, such as learning and perception, which are central issues in many research topics throughout the CoE. We apply the results in computer vision and object recognition, and in robotics to study task-driven modelling of cognitive functions from computational neuroscience perspective.

Cognitive and Social Systems

In Cognitive Systems we will mathematically combine data obtained using complementary non-invasive neuroimaging methods, to disclose dynamic neuronal interactions within and between brain areas. Based on the data and its analysis, we aim to develop an integrated computational model to predict how those interactions give rise to emotion-motivated (goal-directed) audio-visual selective attention. In Social Systems the structure and dynamics of social networks will be analyzed and modelled based on complex networks and agent based approaches.

Computational Systems Biology

Computational systems biology is a new and rapidly developing field of research with focus to understand structure and processes of biological systems at molecular, cellular, tissue and organ level, through computational modeling and novel information theoretic data- and image analysis methods. With the break-through in deciphering the human genome using the most up-to-date computational approaches and modern experimental biotechnology, it has become possible to understand the structure and functions of bio-molecules, information stored in DNA (bioinformatics), its expression to proteins, protein structures (proteomics), metabolic pathways and networks, intra- and inter-cell signaling, and the physico-chemical mechanisms involved in them (biophysics).

There is currently wide interest in biology and biomedicine in structures, relations and functions of biological systems, which we study with a wide at-site-arsenal of state-of-the-art information theoretic analysis and multiscale modelling methods. One of our main interests is high density lipoprotein particles, the carriers of good cholesterol in the blood stream, and reverse cholesterol transport related to the particle structure and function. In addition, the structural aspects of low density lipoprotein particles, the carriers of bad cholesterol, will be tackled via spectroscopy (NMR) and imaging (cryo-electron microscopy) experiments. In the systems biology research LCE’s wide repertoire of information theoretic data and image analysis methods serve as key approaches.

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