computational
modeling in biology

• To generate accurate, quantitative data from single cell time lapse microscopy, we carefully postprocess the images from the wet lab. We normalize and quantify fluorescence and bright field images, which gives us dynamic information about protein levels and morphological cell properties. Currently, we develop a auto-tracking method to speed up cell tracking and to generate unbiased single cell data of full populations. 
• Based on time-dependent expression profiles of mRNA and miRNA data we developed a Bayesian method to infer Boolean gene regulatory networks. The output of the method is not only a single 'best' model but a full statistical model of the parameter space. By analyzing this parameter space we were able to predict several unknown gene-gene and gene-miRNA interactions, which have in part already been experimentally confirmed by the Götz group.
• We modeled the development of hematopoietic stem cells in a multi-scale approach: On a meso scale, we used semantic text-mining to create a transcription factor network which describes myeloid differentiation using boolean modeling techniques.  On a small scale, we studied the dynamics of a gene switch within this network. Contrary to the expectation from a deterministic description, a stochastic model of this switch with only few mRNAs shows complex multi-attractor dynamics without autoactivation and cooperativity.

Funding

• Helmholtz Alliance on Systems Biology (project 'CoReNe')
• German Science Foundation DFG (SPP 1356 'Pluripotency and CellularReprogramming')
• http://www.helmholtz-muenchen.de/en/cmb/funding/erc-starting-grant/index.html ERC Starting-Grant LatentCauses

Collaboration partners

• Magdalena Götz (Neural Stem Cells Group)
• Heiko Lickert (Endoderm Development Group)
• Timm Schroeder (Research Unit Stem Cell Dynamics)

References

• Efficient fluorescence image normalization for time lapse movies
  M. Schwarzfischer, C. Marr, J. Krumsiek, P. S. Hoppe, T. Schroeder, F. J. Theis
  In Proc. Microscopic Image Analysis with Applications in Biology, Heidelberg, Germany, 2011.
• Stability and multi-attractor dynamics of a toggle switch based on a two-stage model of gene expression
  M. Strasser, F. J. Theis, and C. Marr
  In Revision, Biophys J, 2011
• Hierarchical Differentiation of Myeloid Progenitors Is Encoded in the Transcription Factor Network
  J. Krumsiek, C. Marr, T. Schroeder, F.J. Theis
  PLoS ONE, 6:e22649, 2011
• An ensemble approach for inferring semi-quantitative regulatory dynamics for the differentiation of mouse embryonic stem cells using prior knowledge
  D. Lutter, P. Bruns, F.J. Theis
  In Advances In Systems Biology, Springer 2011