The emergence of systems biology signaled a shift of focus, away from the molecular characterization of individual components, towards an understanding of functional activity. The field is however also too focused on pathway-centric approaches, mechanistic models and subcellular processes. It is increasingly evident that the behavior of cells is largely dependent upon influences from the environment. New approaches are thus required to integrate processes at the molecular and cell level with those at higher levels of structural and functional organization (e.g. tissues and tissue physiology). We argue that this calls for a rethinking of what systems biology should be about (the search for organizing principles) and that new approaches are required to tackle biological complexity. To this end we promote Mathematical General Systems Theory, multilevel modeling, and theorem proving as a way forward. In this project we are going to discuss the role of mathematical models, the notion of mechanisms and biological complexity in systems biology.

It is widely assumed that mitochondrial dysfunction and subsequent ROS (Reactive Oxygen Species) production are crucial players in ageing. However, the specific role of mitochondrial pathways in the onset and progression of degeneration and ageing is still unclear, as is the degree of interplay among organs in the ageing process. We hypothesise that impairing mitochondrial respiratory function leads to oxidative stress and ROS production. This induces DNA damage, inflammation and, ultimately, cell senescence and ageing.

Clostridium are bacteria which evolved before the earth had an oxygen atmosphere. To them the air we breathe is a poison. To survive they produce a spore resting stage, resistant to physical and chemical agents. Some species cause devastating diseases, such as the superbug Clostridium difficile. On the other hand, most are totally harmless, and make a wide range of chemicals useful to man. The best example is Clostridium acetobutylicum which makes butanol.

The adult tissue of an organism includes stem cells, which through cell division cycles maintain and regenerate the functional tissue through differentiation and maturation. With regard to stem cell dynamics our research focus is on multilevel systems. Multilevelness is a defining characteristic of complex systems. The behavior of the system ‘as a whole’ is considered to emerge from the functioning and interactions of its parts. What we are seeking is a conceptual (mathematical) framework to analyse how the “fate” of the tissue is an emergent property that inherently arises from the complex yet robust underlying biology of stem cells. Without specifying how the emergence takes place, the concept has almost a mystical character; it is an observation rather than a contribution to understanding the phenomenon. For understanding it is necessary to identify how the behavior of the whole changes when the parts and/or interactions between them change. Understanding cross-level relations in complex systems is key to “demystifying” the concept of emergence.

The PROMICS project addresses the cellular biology and metabolic integration of photorespiratory processes in the context of carbon metabolism (C3, C4 and cyanobacteria), stress response and productivity. The photorespiration is the result of the oxygenase pathway, see the picture below, of the rubisco (ribulose-1,5-bisphosphate carboxylase/oxygenase) which leads to the reduced rates of photosynthetic CO2 assimilation, making photorespiration a wasteful process. However, it is just this inefficiency which can significantly decrease the photoinhibition or high temperature stress. The question arises where is the balance between the protection and crop yield or if the photorespiration is essential process at all.

Protection of humans from the adverse effects of ionizing radiation is a major goal of the Radiation Protection field. In the case of accidental exposures to radiation the development of effective counter measures requires information on the actual exposure dose as well as knowledge on the individual radiosensitivity of the exposed group of individuals. The major scientific goal of this project is to identify suitable sub-sets of genes which correspond to the expression patterns and correlate this information with radiation dose and radiation quality. In addition, it will investigate the effects of single nucleotide polymorphisms on the individual radiation susceptibility and their influence on the proposed biodosimetry system.

Alzheimer's disease (AD) is a neurodegenerative disorder characterized by amyloid plaques in the brain of affected individuals. This project aims at modelling of neurodegenerative processes in AD. Our study focuses on the interactome of neuronal factors central to the proteolytic processing of amyloid precursor protein (APP) into Aβ, the main constituent of senile plaques. Factors considered in this model include proteases, trafficking adaptors, as well as a novel sorting receptor SORLA.

The ability of regeneration characterizes cell biological systems and is increasingly required for computer science systems as well. The Graduate School "dIEM oSiRiS" is a DFG-funded research training group. It brings together researchers from Medicine, Biology and Computer Science and contributes towards achieving new insights into the functioning of biological cell systems, establishing modelling and simulation as an experimental methodology in Biology, and developing innovative modelling and simulation methods and tools from which the understanding and the design of regenerative systems in general will benefit.

Aβ aggregation inside the brain is one major aspect of Alzheimer's disease. The appearance of Aβ plaques is highly correlated with the decline of brain activity. It is therefore necessary to understand the mechanisms regulating Aβ production, Aβ degradation and removal from the brain. The aim of the project is to develop an integrated model to understand the dynamics of Aβ aggregation and its transport through the blood brain barrier.

ExCell is a joint project investigating the changed understanding of the living cell in science. The task for the project partners is to investigate the transformation of scientific knowledge in the life sciences in a comprehensive and interdisciplinary way. For the first time, the shift in paradigm, concerning the understanding of cellular processes in the context of the digital revolution in light microscopy and systems biology, is scrutinized.

The BaCell project is part of the SysMo transnational network, an initiative focusing on approaches on the application of Systems Biology to microorganisms. In the BaCell project, our interest is to gain a better understanding of the dynamics of the transition from exponential to stationary growth phase in Bacillus subtilis. Obtaining knowledge in this model organism provides twofold advances: First, elucidating the fundamental processes in bacterial growth and stress response. Second, Bacillus subtilis is used in many biotechnological applications, thus our research improves production of medical drugs and consumer goods.

Standardization efforts and the exchange of protocols to generate data in the life sciences have become a necessity for large scale projects and multinational collaborations. Data in the life sciences are highly context dependent and if the processes by which the data were generated are not sufficiently well documented, it becomes difficult to reproduce these results and to share and integrate results across projects. The same arguments apply to the generation of scientific results that are based on mathematical models and computer simulations. Systems biology is a scientific approach characterized by an iterative cycle of data-driven modelling and model-driven experimentation. The present project is to provide support for this iterative cycle through techniques and tools that improve and ease the working with simulation setups.

This project combines theoretical and experimental systems biology to challenge pancreatic cancer (PC), a tumour disease with a very poor prognosis. It is focused on mathematical modelling of chemical kinetics and transport processes in biochemical reaction networks of PC cells. The model properties are analysed with methods of dynamical systems theory and methods of experimental design to understand, predict and improve the cellular response to chemotherapy. This effort is supported by quantitative cell biology, and the development of experimental techniques for systems biology.