Life is based on robust networks of interacting biomolecules which mediate and regulate cellular processes. Networks are responsive to many different internal and environmental signals to control higher-level cellular functions like growth, proliferation, differentiation, motility, or apoptosis, and often involve decision-making biochemical reactions. Understanding the structure and functional dynamics of such networks contributes to a basic understanding of biology. It is also important for issues related to health and disease (The Circuits of Life).
The Regulatory Biology Group explores ways to identify regulatory networks, to determine their structure (topology), and to analyse their function in terms of dynamic behaviour.
We focus on three basic tasks:
- Identify, on a systematic basis, molecular building blocks (the nodes) of signaling networks
- Find out how they are functionally interconnected (wired up) and reconstruct the network topology
- Analyse the dynamic behaviour of the interacting molecules to understand its functional relevance
These tasks are addressed through a combination of experimental and computational approaches performed in the lab and in cooperation with both theoreticians and molecular biologists. Doing research on two model organisms, Halobacterium salinarum and Physarum polycephalum we learned how to analyse networks of highly different molecular complexity.
We also develop Petri net based computational approaches for biomodel engineering, simulation, and reverse engineering of signalling and gene regulatory networks.
- Schaap P. et al. 2015. The Physarum polycephalum Genome Reveals Extensive Use of Prokaryotic Two-component and Metazoan-type Tyrosine Kinase Signaling. Genome Biol Evol published online November 27, 2015, : evv237v1-evv237.
- Blätke M.A., M. Heiner and W. Marwan. 2015. BioModel Engineering with Petri Nets. Algebraic and Discrete Mathematical Methods for Modern Biology (ed. R Robeva), pp. 141-192. Academic Press, Burlington.
- Rätzel V.,W. Marwan. 2015. Gene expression kinetics in individual plasmodial cells reveal alternative programs of differential regulation during commitment and differentiation. Develop Growth Differ 57: 408Ð420.
- Soldatova, L.N., D. Nadis, R.D. King, P.S. Basu, E. Haddi, V. Baumle, N.J. Saunders, W. Marwan, and B.B. Rudkin. 2014. EXACT2: the semantics of biomedical protocols. BMC Bioinformatics 15, no. Suppl 14: S5.
- Blätke M.A., C. Rohr, M. Heiner and W. Marwan. 2014. A Petri-Net-Based Framework for Biomodel Engineering. In Large-Scale Networks in Engineering and Life Sciences (pp. 317-366). Springer International Publishing.
- Liu, F., M. Blätke, M. Heiner and M. Yang. 2014. Modelling and simulating reaction diffusion systems using coloured Petri nets. Computers in biology and medicine, 53, 297-308.
- Favre, C.F. and W. Marwan, and A. K. Wagler. 2014. Integrating prior knowledge in automatic network reconstruction. In Proc. of the 5th International Workshop on Biological Processes & Petri Nets (BioPPN), satellite event of Petri Nets 2014, CEUR-WS.org, CEUR Workshop Proceedings, volume 1159, pages 145-59.
- Walter P., X.-K. Hoffmann, B. Ebeling, M. Haas and W. Marwan. 2013. Switch-like reprogramming of gene expression after fusion of multinucleate plasmodial cells of two Physarum polycephalum sporulation mutants. Biochemical and Biophysical Research Communications, 435: 88 - 93.
- Durzinsky M., W. Marwan and A. Wagler. 2013. Reconstruction of extended Petri nets from time-series data by using logical control functions J. Math. Biol. 66:203-223.
- Blätke M.A., A. Dittrich, C. Rohr, M. Heiner and W. Marwan 2013. JAK/STAT signalling - an executable model assembled from molecule-centred modules demonstrating a module-oriented database concept for systems and synthetic biology. Molecular Biosystems
- Rätzel V., B. Ebeling, X. Hoffman, J. Tesmer and Marwan W. 2013. Physarum polycephalum mutants in the photocontrol of sporulation display altered patterns in the correlated expression of developmentally regulated genes. Development, Growth & Differentiation 55 (2), pp. 247 - 259
- Marwan W. and M. Blätke 2012. A module-based approach to biomodel engineering with Petri nets. In Proceedings of the 2012 Winter Simulation Conference (WSC 2012), Berlin, IEEE, 978-1-4673-4781-5/12, 2012.
- Blätke M., M. Heiner and W. Marwan 2012. Predicting Phenotype from Genotype through Automatically Composed Petri Nets Proc. 10th International Conference on Computational Methods in Systems Biology (CMSB 2012), London, Springer, LNCS/LNBI, volume 7605, pp. 87 - 106
- Blätke M., A. Dittrich, M. Heiner, F. Schaper and W. Marwan 2012. JAK-STAT Signalling as Example for a Database-Supported Modular Modelling Concept Proc. 10th International Conference on Computational Methods in Systems Biology (CMSB 2012), London, Springer, LNCS/LNBI, volume 7605, pp. 362-365
- Barrantes I., J. Leipzig and W. Marwan. 2012. A Next-Generation Sequencing Approach to Study the Transcriptomic Changes During the Differentiation of Physarum at the Single-Cell Level Gene Regulation and Systems Biology 2012:6 127-137
- Hoffmann X., J. Tesmer, M. Souquet and W. Marwan. 2012. Futile attempts to differentiate provide molecular evidence for individual differences within a population of cells during cellular reprogramming. FEMS Microbiology Letters, Online First, 15 February 2012.
- Marwan W., C. Rohr and M. Heiner. 2012. Petri nets in Snoopy: A unifying framework for the graphical display, computational modelling, and simulation of bacterial regulatory networks in Methods in Molecular Biology, Springer 804/2012:409-437.
Magdeburg Centre for Systems Biology
The Magdeburg Center for Systems Biology (MaCS) was founded in 2007 as a joint project of the University of Magdeburg and the Max Planck Institute for Dynamics of Complex Technical Systems. MaCS is one of four German research centres in Systems Biology that have been funded with financial support of the Federal Ministry of Education and Research (BMBF). MaCS focusses on the development of new aproaches in systems biology and their application to the analysis and reconstruction of molecular networks involved in signal processing and regulation of cellular processes. The goal is the establishment of new, broadly applicable concepts for modeling and systems analysis with reliability at different levels of molecular and functional complexity. Various pro- and eukaryotic model systems with relevance in basic, biomedical, or biotechnological research are investigated.