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Projekt Druckansicht

Diskret-ereignisorientierte Mehrebenenmodellierung und Simulation für die Systembiologie

Fachliche Zuordnung Theoretische Informatik
Förderung Förderung von 2005 bis 2012
Projektkennung Deutsche Forschungsgemeinschaft (DFG) - Projektnummer 13798554
 
Erstellungsjahr 2012

Zusammenfassung der Projektergebnisse

The goal of the project DiEr MoSiS has been in contributing to multi-level modeling and simulation in systems biology. The contributions focus on: • exploring requirements for and the benefits of multi-level modeling and simulation, and the potential and limitations of existing approaches, • developing approaches towards supporting hierarchical composition and reuse of models, • developing modeling approaches for multi-level modeling, i.e., modeling formalisms that emphasize the view of cell biological systems as hierarchically composed reactive systems and modeling formalisms that emphasize the view of cell biological systems as biochemical reactions that apply to hierarchically composed entities, • support for efficiently experimenting with cell biological models, • realizing (based on wet-lab data) a multi-level model which analyses the impact of the heterogeneity of cell population, cell cycle dynamics, and autocrine (or paracrine) mechanisms on the Wnt signalling pathway in neural progenitor cells and offers new hypothesis to be tested in the wet-lab. The project has resulted in a better understanding of the role of multi-level modeling in systems biology, methodological requirements and challenges for supporting multi-level modeling and simulation in systems biology, and has fostered a series of interesting methodological approaches that further research can build upon. • Our modeling and simulation studies underline the importance of taking intra-, inter-ceUular and cell populations' dynamics into account. • Important features for describing multi-level models from biochemical dynamics up to the cell's and population dynamics have been identified. To those belong attributing species, defining reaction constraints on species, and nesting species. Thereby, downward and upward causation between levels become explicit. • In developing modeling formalisms and simulators and in evaluating the performance of simulators the modeling and simulation framework JAMES II and its plug-in based design has proved to be invaluable. • Multi-level rule-based approaches, like ML-Rules, allow a compact description of cellular systems at multiple levels and thus, appear as a promising starting point for continuing research on multi-level modeling and simulation. • Although advances to a more efficient simulation of cell biological models have been made, the calculation effort of multi-level models still hampers a thorough experimentation with multi-level models. The research has received public attention, e.g., • Carsten Maus was part of the team of four that won, based on a multi-level modeling approach, the Second International Bio-modelling Competition which was organized as part of the Dagstuhl Seminar 11151. The used approach utilized and combined diverse deterministic and stochastic methods to synchronize gene expression in cell populations. • The publication of ML-Rules in BMC Systems Biology has been greeted by a commentary in BMC Biology, 2011, 9:68 "Toward a comprehensive language for biological systems" authored by James Paeder, both commentary and publication on ML-Rules have been rated as being highly accessed.

Projektbezogene Publikationen (Auswahl)

  • Combining micro and macro-modeling in DEVS for computational biology. In: S. G. Henderson, B. Biller, M.-H. Hsieh, J. Shortle, J. D. Tew, and R. R. Barton, editors, WSC '07: Proceedings of the 39th Winter simulation conference, pages 871-880. IEEE Press, 2007
    Adelinde M Uhrmacher, Roland Ewald, Mathias John, Carsten Maus, Matthias Jeschke, and Susanne Biermann
  • Discrete event modelling and simulation in systems biology. Journal of Simulation, 1(2):81-96, 2007
    Roland Ewald, Carsten Maus, Arndt Rolfs, and Adelinde M Uhrmacher
  • A bounded-optimistic, parallel beta-binders simulator. In: Abdulmotaleb El Saddik, David Roberts, and Alois Ferscha, editors. Proceedings of the 12th IEEE International Symposium on Distributed Simulation and Real-Time Applications, pages 139-148. IEEE Computer Society, IEEE Press, 2008
    Stefan Leye, Corrado Priami, and Adelinde M. Uhrmacher
  • Component-based modelling of RNA structure folding. In: Computational Methods in Systems Biology, International Conference, CMSB 2008, Rostock, Germany, October 12-15, 2008, Proceedings, volume 5307 of Lecture Notes in Computer Science, pages 44-62, Berlin/Heidelberg, 2008. Springer
    Carsten Maus
  • Definition and analysis of composition structure for discrete-event models. In: S.J. Mason, R.R. Hill, L. Moench, and O. Rose, editors, Proceedings of the 2008 Winter Simulation Conference, pages 942-950, 2008
    Mathias Röhl and Adelinde M Uhrmacher
  • Hierarchical modeling for computational biology. In: Marco Bernardo, Pierpaolo Degano, and Gianluigi Zavattaro, editors, SFM 2008, Formal Methods for Computational Systems Biology, Lecture Notes in Computer Science, pages 81-124. Springer, Berlin Heidelberg, 2008
    Carsten Maus, Mathias John, Mathias Röhl, and Adelinde M Uhrmacher
  • Parallel and distributed spatial simulation of chemical reactions. In: Proceedings of the 22nd ACM/IEEE/SCS Workshop on Principles oj Advanced and Distributed Simulation (PADS 2008), pages 51-59, 2008
    Matthias Jeschke, Alfred Park, Roland Ewald, Richard Fujimoto, and Adelinde M Uhrmacher
  • Integrating diverse reaction types into stochastic models - a signaling pathway case study in the imperative pi-calculus. In: M. D. Rossetti, R. R. Hill, B. Johansson, A. Dunkin, and R. G. Ingalls, editors, Proceedings of the Winter Simulation Conference, pages 932-943. IEEE Computer Science, 2009
    Orianne Mazemondet, Mathias John, Carsten Maus, Adelinde M Uhrmacher, and Arndt Rolfs
  • Flexible experimentation in the modeling and simulation framework JAMES II - implications for computational systems biology. Briefings in Bioinformatics, 11(3):290-300, 2010
    Roland Ewald, Jan Himmelspach, Matthias Jeschke, Stefan Leye, and Adelinde M Uhrmacher
  • Exploring the performance of spatial stochastic simulation algorithms. Journal of Computational Physics, 230(7):2562- 2574, 2011
    Matthias Jeschke, Roland Ewald, and Adelinde M Uhrmacher
  • Rule-based multi-level modeling of cell biological systems. BMC Systems Biology, 5(166), 2011
    Carsten Maus, Rybacki Stefan, and Adelinde M Uhrmacher
 
 

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