Interdisziplinäres Zentrum
für Bioinformatik


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Multicellular systems


The research group Multicellular systems focuses on the understanding of tissue formation on different time and length scales. It pursues projects on the development of models to permit realistic simulations of multicellular organization processes, and on the analysis of data that occur during this processes.

Group leader: Dirk Drasdo
Members: Stefan Höhme, Nick Jagiella, Axel Krinner
Group website: For further information and details, please refer to our project website.


Many diseases become manifest at the multi-cellular level. In such cases the analysis of the intracellular regulatory processes is insufficient both to understand the mechanisms that led to the diseases and to optimize their therapy.We use methods from Computer Science, Physics and Mathematics to analyze and model multicellular systems on different lengths and time scales.

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The major aims of the Research Group are:


A: The development of mathematical tissue models at different hierarchical levels. The model development is in each case guided by biological questions.
B: The applications of the models.
C: The data analysis at the interface between experiments and modeling.
     

A: Structure formation in tissues as well as mal-functions on the multi-cellular level are inherently of multi-scale nature. Modifications on the molecular level by intrinsic or extrinsic factors affect the architecture and function on the multi-cellular tissue level. Much of the current research so far focuses on the analysis of intracellular pathways, genetic and metabolic regulation on the intracellular scale and on continuum equations for local densities of cells to capture multi-cellular objects on large spatial scalesbut only recently increasing effort is made on the interface between both: individual cell based models (IBMs) which permit to include the molecular information on one hand and to extrapolate to the multi-cellular tissue level on the other hand. In order to bridge the existing gap we have studied different approaches:

  • intracellular regulation networks
  • lattice-free IBMs
  • cellular automaton (CA) models
  • continuum models
 

B: Besides the methodical aspects we focus on a number of applications:

  • unstructured cell populations growing in monolayer
  • multicellular spheroids
  • biotechnological applications such as the optimization of cell yield of MDCK-cells
    for vaccine production
  • complex tissue architectures in regenerative tissues such as the regeneration of
    liver lobules after toxic damage

The applications are guided by quantitative comparisons to experimental data either from published knowledge or generated by experimental partners.

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C: The adjustment of the models developed in (A) to applications requires data analysis both, of molecular data such as gene expression profiles and of image data such as spatial-temporal growth pattern. For this purpose we recently considered:

  • on the molecular level the reconstruction of gene regulatory networks from
    single cell expression data
  • on the multi-cellular level the geometric and topological measures to quantify tumor shapes
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